Relevant bibliographies by topics / Physical Computing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Physical Computing'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 January 2023

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Journal articles on the topic "Physical Computing"

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Hecht, Jeff. "Physical Limits of Computing." Computers in Physics 3, no. 4 (1989): 34. http://dx.doi.org/10.1063/1.4822857.

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Rosenbloom, Andrew. "Computing the physical infrastructure." netWorker 13, no. 3 (2009): 3. http://dx.doi.org/10.1145/1600303.1600304.

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Ananthanarayan, Swamy, and Susanne Boll. "Physical computing for children." Interactions 27, no. 3 (2020): 40–45. http://dx.doi.org/10.1145/3386235.

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Wolpert, David, H. Pierre Noyes, and Rolf Landauer. "Reversible Computing and Physical Law." Physics Today 45, no. 3 (1992): 98–100. http://dx.doi.org/10.1063/1.2809599.

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Fry, Robert. "Physical Intelligence and Thermodynamic Computing." Entropy 19, no. 3 (2017): 107. http://dx.doi.org/10.3390/e19030107.

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Frank, M. P. "The physical limits of computing." Computing in Science & Engineering 4, no. 3 (2002): 16–26. http://dx.doi.org/10.1109/5992.998637.

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PRZYBYLLA, Mareen, and Ralf ROMEIKE. "Physical Computing and its Scope - Towards a Constructionist Computer Science Curriculum with Physical Computing." Informatics in Education 13, no. 2 (2014): 225–40. http://dx.doi.org/10.15388/infedu.2014.14.

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Fujita, Kenichi, Syogo Yonekura, Satoshi Nishikawa, Ryuma Niiyama, and Yasuo Kuniyoshi. "Environmental and Structural Effects on Physical Reservoir Computing with Tensegrity." Journal of the Institute of Industrial Applications Engineers 6, no. 2 (2018): 92–99. http://dx.doi.org/10.12792/jiiae.6.92.

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Horsman, Clare, Susan Stepney, Rob C. Wagner, and Viv Kendon. "When does a physical system compute?" Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 470, no. 2169 (2014): 20140182. http://dx.doi.org/10.1098/rspa.2014.0182.

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Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or not; leading to confusion over novel computational devices, and even claims that every physical event is a computation. In this paper, we introduce a formal framework that can be used to determine whether a physical system is performing a computation. We demonstrate how the abst
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임찬 and 박찬주. "Interactive contents development utilizing physical computing." Journal of Digital Design 13, no. 1 (2013): 681–90. http://dx.doi.org/10.17280/jdd.2013.13.1.065.

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Dissertations / Theses on the topic "Physical Computing"

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Lerner, Lee Wilmoth. "Trustworthy Embedded Computing for Cyber-Physical Control." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/51545.

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A cyber-physical controller (CPC) uses computing to control a physical process. Example CPCs can be found in self-driving automobiles, unmanned aerial vehicles, and other autonomous systems. They are also used in large-scale industrial control systems (ICSs) manufacturing and utility infrastructure. CPC operations rely on embedded systems having real-time, high-assurance interactions with physical processes. However, recent attacks like Stuxnet have demonstrated that CPC malware is not restricted to networks and general-purpose computers, rather embedded components are targeted as well. G
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Kaivo, Melissa. "Supporting Learning Physical Computing Through Design Activities." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20527.

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Students and teachers encounter new challenges as Nordic countries, and many other countries decided to implement computational thinking and programming into the compulsory education curriculum. Likewise, universities have modified programmes to respond to the skills required in the future’s digital world. Computational thinking is nowadays a fundamental skill for problem-solving, and to successfully implement it to education, new approaches and methods need to be developed. This paper explored the use of a physical computing platform called Arduino as a means of introducing computational thin
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Schulz, Sandra. "Physical Computing als Mittel der wissenschaftlichen Erkenntnisgewinnung." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19620.

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Physical-Computing-Geräten wie Robotern und Mikrocontrollern wird eine wichtige Rolle als Lernmedium für Schülerinnen und Schüler zugesprochen. Zu lernende Kontexte sind ähnlich vielfältig wie die inzwischen existierenden Geräte. Die Komplexität der Systeme ist mannigfaltig und bisherige Forschung geht zumeist von dem Gerät als Forschungsgegenstand aus. Im Rahmen dieser Dissertation wird von einem geräteunabhängigen Physical- Computing-Prozess als Problemlöseprozess ausgegangen, um ein Fundament für nachhaltige und geräteunabhängige Forschung zu schaffen sowie Physical Computing als Unte
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Stewart, Sean. "Deploying a CMS Tier-3 Computing Cluster with Grid-enabled Computing Infrastructure." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2564.

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The Large Hadron Collider (LHC), whose experiments include the Compact Muon Solenoid (CMS), produces over 30 million gigabytes of data annually, and implements a distributed computing architecture—a tiered hierarchy, from Tier-0 through Tier-3—in order to process and store all of this data. Out of all of the computing tiers, Tier-3 clusters allow scientists the most freedom and flexibility to perform their analyses of LHC data. Tier-3 clusters also provide local services such as login and storage services, provide a means to locally host and analyze LHC data, and allow both remote and local us
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Park, C. (Chaeah). "Triggering women’s interest in programming within physical computing context." Master's thesis, University of Oulu, 2018. http://urn.fi/URN:NBN:fi:oulu-201811103022.

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In spite of numerous educational practices and initiatives in programming (Rubio, Romero-Zaliz, Mañoso, & Angel, 2015), women show less participation in learning programming compared to men (Faulkner & McClard, 2014; Harris, 2014). Lack of interest and motivation could explain the gender gap (Faulkner & McClard, 2014; Fisher & Margolis 2002). Interest can be raised and kept high by a variety of triggers, therefore they are salient motivational factors, which can lead to motivation and finally to engagement (Kangas, Siklander, Randolph, & Ruokamo, 2017; Krapp, 2003; Renninger & Bachrach, 2015;
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Furrer, Frank J., and Georg Püschel. "From Algorithmic Computing to Autonomic Computing." Technische Universität Dresden, 2018. https://tud.qucosa.de/id/qucosa%3A30773.

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In algorithmic computing, the program follows a predefined set of rules – the algorithm. The analyst/designer of the program analyzes the intended tasks of the program, defines the rules for its expected behaviour and programs the implementation. The creators of algorithmic software must therefore foresee, identify and implement all possible cases for its behaviour in the future application! However, what if the problem is not fully defined? Or the environment is uncertain? What if situations are too complex to be predicted? Or the environment is changing dynamically? In many such cases algor
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Guymon, Daniel Wade. "Cyber-physical Algorithms for Enhancing Collaboration." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/31919.

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The research presented in this thesis covers two specific problems within the larger domain of cyber-physical algorithms for enhancing collaboration between one or more people. The two specific problems are 1) determining when people are going to arrive late to a meeting and 2) creating ad-hoc secure pairing protocols for short-range communication. The domain was broken down at opposite extremes in order to derive these problems to work on: 1) collaborations that are planned long in advance and deviations from the plan need to be detected and 2) collaborations that are not planned and need t
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Li, Xinfeng. "Time-sensitive Information Communication, Sensing, and Computing in Cyber-Physical Systems." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397731767.

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Meiners, Justin. "Computing the Rank of Braids." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/8947.

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We describe a method for computing rank (and determining quasipositivity) in the free group using dynamic programming. The algorithm is adapted to computing upper bounds on the rank for braids. We test our method on a table of knots by identifying quasipositive knots and calculating the ribbon genus. We consider the possibility that rank is not theoretically computable and prove some partial results that would classify its computational complexity. We then present a method for effectively brute force searching band presentations of small rank and conjugate length.
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Sonnabaum, Mark. "Modern Api Design and Physical Computing Techniques in Just Intonation Performance Practice." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc271901/.

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approached previously by both Harry Partch and Ben Johnston, and proposes the decoupling of interface and sound production as a way forward. The design and implementation of a software instrument and a hardware prototype are described, both using a simple API for variable tuning instruments. The hardware prototype uses physical computing techniques to control the tuning of a string with a servo motor, while the software instrument exists entirely in a web browser. Finally, potential algorithms for clients of the API are presented, and the effectiveness of the hardware prototype is evaluated by
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Books on the topic "Physical Computing"

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Physical computing and makerspaces. Rosen Central, 2015.

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Tom, Igoe, ed. Physical computing: Sensing and controlling the physical world with computers. Thomson, 2004.

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Timms, Howard. Measuring and computing. Gloucester Press, 1989.

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Hahanov, Vladimir. Cyber Physical Computing for IoT-driven Services. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-54825-8.

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1942-, Ohmi Tetsuo, ed. Quantum computing: From linear algebra to physical realizations. CRC Press, 2008.

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Nakahara, Mikio. Quantum computing: From linear algebra to physical realizations. Taylor & Francis, 2008.

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Möller, Dietmar P. F. Guide to Computing Fundamentals in Cyber-Physical Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25178-3.

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Dougherty, Edward R. Probability and statistics for theengineering, computing, and physical sciences. Prentice Hall, 1990.

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Odendahl, Manuel. Arduino - Physical Computing fu r Bastler, Designer und Geeks. 2nd ed. O'Reilly, 2010.

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Dougherty, Edward R. Probability and statistics for the engineering, computing, and physical sciences. Prentice Hall, 1990.

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Book chapters on the topic "Physical Computing"

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Hahanov, Vladimir, Eugenia Litvinova, Svetlana Chumachenko, and Anna Hahanova. "Cyber Physical Computing." In Cyber Physical Computing for IoT-driven Services. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-54825-8_1.

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Lyu, Shing. "Physical Computing in Rust." In Practical Rust Projects. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5599-5_5.

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Belojevic, Nina, and Shaun Macpherson. "Physical Computing, Embodied Practice." In The Routledge Companion to Media Studies and Digital Humanities. Routledge, 2018. http://dx.doi.org/10.4324/9781315730479-26.

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Dittrich, Thomas. "Physical Aspects of Computing." In Information Dynamics. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96745-1_9.

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Hauser, Helmut. "Physical Reservoir Computing in Robotics." In Natural Computing Series. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-13-1687-6_8.

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Good, Donald I. "Computing is a physical science." In VDM '88 VDM — The Way Ahead. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-50214-9_1.

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Nazemi, Mark. "Sonic Interaction With Physical Computing." In Foundations in Sound Design for Embedded Media. Routledge, 2019. http://dx.doi.org/10.4324/9781315106359-1.

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Sarkar, Kanchan, and Sankar Prasad Bhattacharyya. "Evolutionary Computing." In Soft-Computing in Physical and Chemical Sciences. CRC Press, 2017. http://dx.doi.org/10.4324/9781315152899-3.

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Murphy, Julian. "Clockless Physical Unclonable Functions." In Trust and Trustworthy Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30921-2_7.

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Zhuge, Hai. "Computing with Known and Unknown." In Cyber-Physical-Social Intelligence. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-7311-4_11.

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Conference papers on the topic "Physical Computing"

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Hahanov, Vladimir, Mazen Abdelrahman Abdelaziz Hussein, Anna Hahanova, and Ka Lok Man. "Cyber physical computing." In 2016 IEEE East-West Design & Test Symposium (EWDTS). IEEE, 2016. http://dx.doi.org/10.1109/ewdts.2016.7807670.

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Ball, Thomas. "Physical computing for everyone." In 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering Education and Training Track (ICSE-SEET). IEEE, 2017. http://dx.doi.org/10.1109/icse-seet.2017.31.

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Boer, Laurens, and Harvey Bewley. "Smörgåsbords for Physical Computing." In TEI '21: Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction. ACM, 2021. http://dx.doi.org/10.1145/3430524.3446077.

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Ishikawa, Fuyuki, Basem Suleiman, Kayoko Yamamoto, and Shinichi Honiden. "Physical interaction in pervasive computing." In the 2009 international conference. ACM Press, 2009. http://dx.doi.org/10.1145/1568199.1568219.

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Zhu, Qianqian, and Andy Zaidman. "Mutation Testing for Physical Computing." In 2018 IEEE International Conference on Software Quality, Reliability and Security (QRS). IEEE, 2018. http://dx.doi.org/10.1109/qrs.2018.00042.

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Schulz, Sandra, and Niels Pinkwart. "Physical Computing in STEM Education." In WiPSCE '15: Workshop in Primary and Secondary Computing Education. ACM, 2015. http://dx.doi.org/10.1145/2818314.2818327.

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Cassinelli, Alvaro, and Daniel Saakes. "Data Flow, Spatial Physical Computing." In TEI '17: Eleventh International Conference on Tangible, Embedded, and Embodied Interaction. ACM, 2017. http://dx.doi.org/10.1145/3024969.3024978.

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Sentance, Sue, Jane Waite, Lucy Yeomans, and Emily MacLeod. "Teaching with physical computing devices." In WiPSCE '17: 12th Workshop in Primary and Secondary Computing Education. ACM, 2017. http://dx.doi.org/10.1145/3137065.3137083.

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Vermillion, Joshua. "Physical Computing without the Computing: Small Responsive Prototypes." In XVIII Conference of the Iberoamerican Society of Digital Graphics - SIGraDi: Design in Freedom. Editora Edgard Blücher, 2014. http://dx.doi.org/10.5151/despro-sigradi2014-0133.

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Jones, Roger, and Dario BARBERIS. "The ATLAS Computing Model." In European Physical Society Europhysics Conference on High Energy Physics. Sissa Medialab, 2010. http://dx.doi.org/10.22323/1.084.0448.

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Reports on the topic "Physical Computing"

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Bennett, Andrew F. Applications of Parallel Computing in Physical Oceanography. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada627882.

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Simmon, Eric, Kyoung-Sook Kim, Eswaran Subrahmanian, et al. A Vision of Cyber-Physical Cloud Computing for Smart Networked Systems. National Institute of Standards and Technology, 2013. http://dx.doi.org/10.6028/nist.ir.7951.

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Kularatne, Dhanushka N., Subhrajit Bhattacharya, and M. Ani Hsieh. Computing Energy Optimal Paths in Time-Varying Flows. Drexel University, 2016. http://dx.doi.org/10.17918/d8b66v.

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Autonomous marine vehicles (AMVs) are typically deployed for long periods of time in the ocean to monitor different physical, chemical, and biological processes. Given their limited energy budgets, it makes sense to consider motion plans that leverage the dynamics of the surrounding flow field so as to minimize energy usage for these vehicles. In this paper, we present two graph search based methods to compute energy optimal paths for AMVs in two-dimensional (2-D) time-varying flows. The novelty of the proposed algorithms lies in a unique discrete graph representation of the 3-D configuration
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Avery, P., and J. Yelton. Computing support for High Energy Physics. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/458889.

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Shamonia, Volodymyr H., Olena V. Semenikhina, Volodymyr V. Proshkin, Olha V. Lebid, Serhii Ya Kharchenko, and Oksana S. Lytvyn. Using the Proteus virtual environment to train future IT professionals. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3760.

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Based on literature review it was established that the use of augmented reality as an innovative technology of student training occurs in following directions: 3D image rendering; recognition and marking of real objects; interaction of a virtual object with a person in real time. The main advantages of using AR and VR in the educational process are highlighted: clarity, ability to simulate processes and phenomena, integration of educational disciplines, building an open education system, increasing motivation for learning, etc. It has been found that in the field of physical process modelling
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Burby, Joshua, Qi Tang, and Romit Maulik. Computing Poincaré maps using physics-informed deep learning. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1643908.

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Baroni, Alessandro. Quantum Computing for Quantum Dynamics in Nuclear Physics. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1846882.

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McFarlane, K. Benchmarks for the SSCL physics detector simulation computing facility. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/6245260.

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Elvira, V. The Future of High Energy Physics Software and Computing. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1898754.

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Gerber, Richard A., and Harvey Wasserman. Large Scale Computing and Storage Requirements for High Energy Physics. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1003817.

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