{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,21]],"date-time":"2026-06-21T00:49:52Z","timestamp":1782002992172,"version":"3.54.5"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031087592","type":"print"},{"value":"9783031087608","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08760-8_11","type":"book-chapter","created":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T03:06:09Z","timestamp":1655780769000},"page":"129-142","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Reducing Memory Requirements of\u00a0Quantum Optimal Control"],"prefix":"10.1007","author":[{"given":"Sri Hari Krishna","family":"Narayanan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Propson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcelo","family":"Bongarti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"H\u00fcckelheim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Hovland","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,6,15]]},"reference":[{"key":"11_CR1","unstructured":"(2022). https:\/\/github.com\/sriharikrishna\/qoc"},{"issue":"3","key":"11_CR2","doi-asserted-by":"publisher","first-page":"C232","DOI":"10.1137\/15M1019222","volume":"38","author":"G Aupy","year":"2016","unstructured":"Aupy, G., Herrmann, J., Hovland, P., Robert, Y.: Optimal multistage algorithm for adjoint computation. SIAM J. Sci. Comput. 38(3), C232\u2013C255 (2016)","journal-title":"SIAM J. Sci. Comput."},{"key":"11_CR3","unstructured":"Baydin, A.G., Pearlmutter, B.A., Radul, A.A., Siskind, J.M.: Automatic differentiation in machine learning: a survey. J. Mach. Learn. Res. 18(153), 1\u201343 (2018). http:\/\/jmlr.org\/papers\/v18\/17-468.html"},{"issue":"2166","key":"11_CR4","doi-asserted-by":"publisher","first-page":"20190049","DOI":"10.1098\/rsta.2019.0049","volume":"378","author":"O Beaumont","year":"2020","unstructured":"Beaumont, O., Herrmann, J., Pallez, G., Shilova, A.: Optimal memory-aware backpropagation of deep join networks. Phil. Trans. R. Soc. A 378(2166), 20190049 (2020)","journal-title":"Phil. Trans. R. Soc. A"},{"key":"11_CR5","unstructured":"Bradbury, J., et al.: JAX: composable transformations of Python+NumPy programs (2018). http:\/\/github.com\/google\/jax"},{"key":"11_CR6","doi-asserted-by":"publisher","first-page":"022326","DOI":"10.1103\/PhysRevA.84.022326","volume":"84","author":"T Caneva","year":"2011","unstructured":"Caneva, T., Calarco, T., Montangero, S.: Chopped random-basis quantum optimization. Phys. Rev. A 84, 022326 (2011). https:\/\/doi.org\/10.1103\/PhysRevA.84.022326","journal-title":"Phys. Rev. A"},{"key":"11_CR7","unstructured":"Chen, T., Xu, B., Zhang, C., Guestrin, C.: Training deep nets with sublinear memory cost. arXiv preprint arXiv:1604.06174 (2016)"},{"key":"11_CR8","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.cma.2014.12.001","volume":"288","author":"EC Cyr","year":"2015","unstructured":"Cyr, E.C., Shadid, J., Wildey, T.: Towards efficient backward-in-time adjoint computations using data compression techniques. Comput. Meth. Appl. Mech. Eng. 288, 24\u201344 (2015)","journal-title":"Comput. Meth. Appl. Mech. Eng."},{"key":"11_CR9","doi-asserted-by":"publisher","first-page":"190501","DOI":"10.1103\/PhysRevLett.106.190501","volume":"106","author":"P Doria","year":"2011","unstructured":"Doria, P., Calarco, T., Montangero, S.: Optimal control technique for many-body quantum dynamics. Phys. Rev. Lett. 106, 190501 (2011). https:\/\/doi.org\/10.1103\/PhysRevLett.106.190501","journal-title":"Phys. Rev. Lett."},{"issue":"1","key":"11_CR10","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1080\/10556789208805505","volume":"1","author":"A Griewank","year":"1992","unstructured":"Griewank, A.: Achieving logarithmic growth of temporal and spatial complexity in reverse automatic differentiation. Optim. Methods Softw. 1(1), 35\u201354 (1992)","journal-title":"Optim. Methods Softw."},{"issue":"1","key":"11_CR11","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1145\/347837.347846","volume":"26","author":"A Griewank","year":"2000","unstructured":"Griewank, A., Walther, A.: Algorithm 799: Revolve: an implementation of checkpointing for the reverse or adjoint mode of computational differentiation. ACM Trans. Math. Softw. 26(1), 19\u201345 (2000). https:\/\/doi.org\/10.1145\/347837.347846","journal-title":"ACM Trans. Math. Softw."},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Griewank, A., Walther, A.: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. No. 105 in Other Titles in Applied Mathematics, 2nd edn. SIAM, Philadelphia (2008). http:\/\/bookstore.siam.org\/ot105\/","DOI":"10.1137\/1.9780898717761"},{"issue":"3","key":"11_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2450153.2450158","volume":"39","author":"L Hascoet","year":"2013","unstructured":"Hascoet, L., Pascual, V.: The Tapenade automatic differentiation tool: principles, model, and specification. ACM Trans. Math. Softw. (TOMS) 39(3), 1\u201343 (2013)","journal-title":"ACM Trans. Math. Softw. (TOMS)"},{"key":"11_CR14","unstructured":"Jain, P., et al.: Checkmate: breaking the memory wall with optimal tensor rematerialization. In: Proceedings of Machine Learning and Systems, vol. 2, pp. 497\u2013511 (2020)"},{"issue":"8","key":"11_CR15","doi-asserted-by":"publisher","first-page":"1760","DOI":"10.1016\/j.cpc.2012.02.021","volume":"183","author":"J Johansson","year":"2012","unstructured":"Johansson, J., Nation, P., Nori, F.: QuTiP: an open-source python framework for the dynamics of open quantum systems. Comput. Phys. Commun. 183(8), 1760\u20131772 (2012). https:\/\/doi.org\/10.1016\/j.cpc.2012.02.021","journal-title":"Comput. Phys. Commun."},{"issue":"4","key":"11_CR16","doi-asserted-by":"publisher","first-page":"1234","DOI":"10.1016\/j.cpc.2012.11.019","volume":"184","author":"J Johansson","year":"2013","unstructured":"Johansson, J., Nation, P., Nori, F.: QuTiP 2: a Python framework for the dynamics of open quantum systems. Comput. Phys. Commun. 184(4), 1234\u20131240 (2013). https:\/\/doi.org\/10.1016\/j.cpc.2012.11.019","journal-title":"Comput. Phys. Commun."},{"key":"11_CR17","doi-asserted-by":"publisher","first-page":"032308","DOI":"10.1103\/PhysRevA.63.032308","volume":"63","author":"N Khaneja","year":"2001","unstructured":"Khaneja, N., Brockett, R., Glaser, S.J.: Time optimal control in spin systems. Phys. Rev. A 63, 032308 (2001). https:\/\/doi.org\/10.1103\/PhysRevA.63.032308","journal-title":"Phys. Rev. A"},{"issue":"2","key":"11_CR18","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1080\/10556789808805717","volume":"10","author":"K Kubota","year":"1998","unstructured":"Kubota, K.: A Fortran77 preprocessor for reverse mode automatic differentiation with recursive checkpointing. Optim. Meth. Softw. 10(2), 319\u2013335 (1998). https:\/\/doi.org\/10.1080\/10556789808805717","journal-title":"Optim. Meth. Softw."},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Kukreja, N., H\u00fcckelheim, J., Louboutin, M., Washbourne, J., Kelly, P.H., Gorman, G.J.: Lossy checkpoint compression in full waveform inversion. Geoscientific Model Development Discussions, pp. 1\u201326 (2020)","DOI":"10.5194\/gmd-2020-325"},{"key":"11_CR20","doi-asserted-by":"publisher","first-page":"042318","DOI":"10.1103\/PhysRevA.95.042318","volume":"95","author":"N Leung","year":"2017","unstructured":"Leung, N., Abdelhafez, M., Koch, J., Schuster, D.: Speedup for quantum optimal control from automatic differentiation based on graphics processing units. Phys. Rev. A 95, 042318 (2017). https:\/\/doi.org\/10.1103\/PhysRevA.95.042318","journal-title":"Phys. Rev. A"},{"key":"11_CR21","doi-asserted-by":"publisher","unstructured":"Naumann, U.: The Art of Differentiating Computer Programs. Society for Industrial and Applied Mathematics (2011). https:\/\/doi.org\/10.1137\/1.9781611972078","DOI":"10.1137\/1.9781611972078"},{"key":"11_CR22","doi-asserted-by":"publisher","unstructured":"Rajbhandari, S., Ruwase, O., Rasley, J., Smith, S., He, Y.: ZeRO-infinity: breaking the GPU memory wall for extreme scale deep learning. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2021. Association for Computing Machinery, New York (2021). https:\/\/doi.org\/10.1145\/3458817.3476205","DOI":"10.1145\/3458817.3476205"},{"issue":"C","key":"11_CR23","doi-asserted-by":"publisher","first-page":"1147","DOI":"10.1016\/j.procs.2016.05.444","volume":"80","author":"M Schanen","year":"2016","unstructured":"Schanen, M., Marin, O., Zhang, H., Anitescu, M.: Asynchronous two-level checkpointing scheme for large-scale adjoints in the spectral-element solver Nek5000. Procedia Comput. Sci. 80(C), 1147\u20131158 (2016). https:\/\/doi.org\/10.1016\/j.procs.2016.05.444","journal-title":"Procedia Comput. Sci."}],"container-title":["Lecture Notes in Computer Science","Computational Science \u2013 ICCS 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08760-8_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,21]],"date-time":"2026-06-21T00:04:41Z","timestamp":1782000281000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08760-8_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031087592","9783031087608"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08760-8_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"15 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"London","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccs-computsci2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iccs-meeting.org\/iccs2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"474","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"175","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"78","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"37% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.8","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}