Navigating the realm where physics intersects with programming, this book serves as an indispensable guide for students embarking on their journey with Julia. Whether it is plotting equations or analyzing experimental data, mastering computational tools is essential for unraveling the complexities of physical phenomena. Julia, an open-source programming language, emerges as the bridge between simplicity and efficiency.
While Python, another open-source language, offers user-friendly syntax, its line-by-line execution often leads to sluggish performance. Julia, however, embodies the ethos of being "as easy as Python but as fast as C/C++," tailored specifically for scientific computing with ongoing developmental enhancements. Notably, Microsoft's AI assistant Copilot is crafted in Julia, showcasing its versatility and adaptability.
Within these pages, readers encounter cutting-edge research illustrating Julia's prowess across diverse domains. From streamlined code composition facilitated by modular architecture to the integration of artificial intelligence and graphical visualization, this book illuminates Julia's multifaceted applications. It notably avoids delving into AI algorithms, instead focusing on equipping readers with foundational Julia skills applicable to physics problem-solving.
Julia boasts an extensive library ecosystem tailored for scientific computing, empowering users with tools for tasks ranging from differential equation solving to statistical analysis. Its robust support for parallel processing enables swift computations on multi-core systems, a crucial asset for handling voluminous datasets with finesse.
Starting with a primer on Julia fundamentals, the book gradually transitions to practical applications across various physics subdomains. From nuclear physics to high-energy phenomena, each chapter offers hands-on exercises that cement comprehension and foster proficiency in employing computational methods to unravel complex physical phenomena.
Designed as a precursor to deeper explorations into AI applications within scientific realms, this book lays the groundwork for harnessing Julia's capabilities in physics-centric contexts.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
R. Gökhan Türeci was born in 1976 in Lüleburgaz. After completing his high school education in 1993, he graduated from Ankara University, Faculty of Science, Department of Physics in 1997. In the same year, he started to work as a research assistant at Kırıkkale University. In 2006, he completed his Ph.D. He is currently working at Kırıkkale University, Kırıkkale Vocational School. He continues his researches by performing scientific calculations in Wolfram Mathematica, Python, and Julia programming languages.
Born in 1975, Hamdi Dağistanli completed his primary, secondary, and high school education in Ankara. In 1998, he graduated from Ankara University, Department of Physics Engineering with the title of Physics Engineer in 1998. Between 1998 and 2005, he completed his master's and doctorate programs at the Institute of Natural and Applied Sciences. During this period, he worked as a research assistant at the same university. During his graduate studies, he worked in the fields of solid-state and atomic molecular physics. Between 2004 and 2013, he served as an officer in the Air Force Command, as a battery commander, and as a lecturer at the Air Non-Commissioned Officer Vocational High School. Since 2013, he has been working as a physics teacher in private schools and colleges as well as a project consultant. He is fluent in English and French.
Prof. Dr. İIlkay Türk Çakir was born in Bolu, Turkey. She graduated from Ankara University, Faculty of Science, Department of Physics in 1994. She completed her Master degree in 1997 and his doctorate in 2003 in the field of High Energy Physics (HEP). Between 1994 and 2002, she has worked as a research assistant in the Department of Physics in Ankara University in the field of HEP. She worked as a researcher at Turkish Atomic Energy Authority between 2003 and 2014. Then she studied as an associate professor in Istanbul Aydin University between 2014 and 2015. In between 2015 and 2022 years, she worked for Energy Systems Engineering Department in Giresun University as a professor. She is currently working on the Institute of Accelerator Technologies at Ankara University as a director. She conducted short- and long-term research at European Nuclear Research Center (CERN)/Geneva.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Navigating the realm where physics intersects with programming, this book serves as an indispensable guide for students embarking on their journey with Julia. Whether it is plotting equations or analyzing experimental data, mastering computational tools is essential for unraveling the complexities of physical phenomena. Julia, an open-source programming language, emerges as the bridge between simplicity and efficiency.While Python, another open-source language, offers user-friendly syntax, its line-by-line execution often leads to sluggish performance. Julia, however, embodies the ethos of being 'as easy as Python but as fast as C/C++,' tailored specifically for scientific computing with ongoing developmental enhancements. Notably, Microsoft's AI assistant Copilot is crafted in Julia, showcasing its versatility and adaptability.Within these pages, readers encounter cutting-edge research illustrating Julia's prowess across diverse domains. From streamlined code composition facilitated by modular architecture to the integration of artificial intelligence and graphical visualization, this book illuminates Julia's multifaceted applications. It notably avoids delving into AI algorithms, instead focusing on equipping readers with foundational Julia skills applicable to physics problem-solving.Julia boasts an extensive library ecosystem tailored for scientific computing, empowering users with tools for tasks ranging from differential equation solving to statistical analysis. Its robust support for parallel processing enables swift computations on multi-core systems, a crucial asset for handling voluminous datasets with finesse.Starting with a primer on Julia fundamentals, the book gradually transitions to practical applications across various physics subdomains. From nuclear physics to high-energy phenomena, each chapter offers hands-on exercises that cement comprehension and foster proficiency in employing computational methods to unravel complex physical phenomena.Designed as a precursor to deeper explorations into AI applications within scientific realms, this book lays the groundwork for harnessing Julia's capabilities in physics-centric contexts. 259 pp. Englisch. N° de réf. du vendeur 9783031847158
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Hardcover. Etat : new. Hardcover. Navigating the realm where physics intersects with programming, this book serves as an indispensable guide for students embarking on their journey with Julia. Whether it is plotting equations or analyzing experimental data, mastering computational tools is essential for unraveling the complexities of physical phenomena. Julia, an open-source programming language, emerges as the bridge between simplicity and efficiency.While Python, another open-source language, offers user-friendly syntax, its line-by-line execution often leads to sluggish performance. Julia, however, embodies the ethos of being "as easy as Python but as fast as C/C++," tailored specifically for scientific computing with ongoing developmental enhancements. Notably, Microsoft's AI assistant Copilot is crafted in Julia, showcasing its versatility and adaptability.Within these pages, readers encounter cutting-edge research illustrating Julia's prowess across diverse domains. From streamlined code composition facilitated by modular architecture to the integration of artificial intelligence and graphical visualization, this book illuminates Julia's multifaceted applications. It notably avoids delving into AI algorithms, instead focusing on equipping readers with foundational Julia skills applicable to physics problem-solving.Julia boasts an extensive library ecosystem tailored for scientific computing, empowering users with tools for tasks ranging from differential equation solving to statistical analysis. Its robust support for parallel processing enables swift computations on multi-core systems, a crucial asset for handling voluminous datasets with finesse.Starting with a primer on Julia fundamentals, the book gradually transitions to practical applications across various physics subdomains. From nuclear physics to high-energy phenomena, each chapter offers hands-on exercises that cement comprehension and foster proficiency in employing computational methods to unravel complex physical phenomena.Designed as a precursor to deeper explorations into AI applications within scientific realms, this book lays the groundwork for harnessing Julia's capabilities in physics-centric contexts. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783031847158
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Navigating the realm where physics intersects with programming, this book serves as an indispensable guide for students embarking on their journey with Julia. Whether it is plotting equations or analyzing experimental data, mastering computational tools is essential for unraveling the complexities of physical phenomena. Julia, an open-source programming language, emerges as the bridge between simplicity and efficiency.While Python, another open-source language, offers user-friendly syntax, its line-by-line execution often leads to sluggish performance. Julia, however, embodies the ethos of being 'as easy as Python but as fast as C/C++,' tailored specifically for scientific computing with ongoing developmental enhancements. Notably, Microsoft's AI assistant Copilot is crafted in Julia, showcasing its versatility and adaptability.Within these pages, readers encounter cutting-edge research illustrating Julia's prowess across diverse domains. From streamlined code composition facilitated by modular architecture to the integration of artificial intelligence and graphical visualization, this book illuminates Julia's multifaceted applications. It notably avoids delving into AI algorithms, instead focusing on equipping readers with foundational Julia skills applicable to physics problem-solving.Julia boasts an extensive library ecosystem tailored for scientific computing, empowering users with tools for tasks ranging from differential equation solving to statistical analysis. Its robust support for parallel processing enables swift computations on multi-core systems, a crucial asset for handling voluminous datasets with finesse.Starting with a primer on Julia fundamentals, the book gradually transitions to practical applications across various physics subdomains. From nuclear physics to high-energy phenomena, each chapter offers hands-on exercises that cement comprehension and foster proficiency in employing computational methods to unravel complex physical phenomena.Designed as a precursor to deeper explorations into AI applications within scientific realms, this book lays the groundwork for harnessing Julia's capabilities in physics-centric contexts.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch. N° de réf. du vendeur 9783031847158
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Navigating the realm where physics intersects with programming, this book serves as an indispensable guide for students embarking on their journey with Julia. Whether it is plotting equations or analyzing experimental data, mastering computational tools is essential for unraveling the complexities of physical phenomena. Julia, an open-source programming language, emerges as the bridge between simplicity and efficiency.While Python, another open-source language, offers user-friendly syntax, its line-by-line execution often leads to sluggish performance. Julia, however, embodies the ethos of being 'as easy as Python but as fast as C/C++,' tailored specifically for scientific computing with ongoing developmental enhancements. Notably, Microsoft's AI assistant Copilot is crafted in Julia, showcasing its versatility and adaptability.Within these pages, readers encounter cutting-edge research illustrating Julia's prowess across diverse domains. From streamlined code composition facilitated by modular architecture to the integration of artificial intelligence and graphical visualization, this book illuminates Julia's multifaceted applications. It notably avoids delving into AI algorithms, instead focusing on equipping readers with foundational Julia skills applicable to physics problem-solving.Julia boasts an extensive library ecosystem tailored for scientific computing, empowering users with tools for tasks ranging from differential equation solving to statistical analysis. Its robust support for parallel processing enables swift computations on multi-core systems, a crucial asset for handling voluminous datasets with finesse.Starting with a primer on Julia fundamentals, the book gradually transitions to practical applications across various physics subdomains. From nuclear physics to high-energy phenomena, each chapter offers hands-on exercises that cement comprehension and foster proficiency in employing computational methods to unravel complex physical phenomena.Designed as a precursor to deeper explorations into AI applications within scientific realms, this book lays the groundwork for harnessing Julia's capabilities in physics-centric contexts. N° de réf. du vendeur 9783031847158
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