'Numerical Inverting of Matrices of High Order,' pp. 1021-1099 in Bulletin of the American Mathematical Society, Vol. 53, No. 11, November, 1947. [Offered with:] 'Numerical Inverting of Matrices of High Order II,' pp. 188-202 in Proceedings of the American Mathematical Society, Vol. 2, No. 2, April, 1951

THE BIRTH OF MODERN NUMERICAL ANALYSIS. First edition, journal issues in the original printed wrappers, of two of von Neumann's major papers. "The 1947 paper by John von Neumann and Herman Goldstine, 'Numerical Inverting of Matrices of High Order' (Bulletin of the AMS, Nov. 1947), is considered as the birth certificate of numerical analysis. Since its publication, the evolution of this domain has been enormous" (Bultheel & Cools). "Just when modern computers were being invented (those digital, electronic, and programmable), John von Neumann and Herman Goldstine wrote a paper to illustrate the mathematical analyses that they believed would be needed to use the new machines effectively and to guide the development of still faster computers. Their foresight and the congruence of historical events made their work the first modern paper in numerical analysis. Von Neumann once remarked that to found a mathematical theory one had to prove the first theorem, which he and Goldstine did concerning the accuracy of mechanized Gaussian elimination - but their paper was about more than that. Von Neumann and Goldstine described what they surmised would be the significant questions once computers became available for computational science, and they suggested enduring ways to answer them" (Grcar, p. 607). "In sum, von Neumann's paper contains much that is unappreciated or at least unattributed to him. The contents are so familiar, it is easy to forget von Neumann is not repeating what everyone knows. He anticipated many of the developments in the field he originated, and his theorems on the accuracy of Gaussian elimination have not been encompassed in half a century. The paper is among von Neumann's many firsts in computer science. It is the first paper in modern numerical analysis, and the most recent by a person of von Neumann's genius" (Vuik). Von Neumann & Goldstine's 1947 paper is here accompanied by its sequel (the 1947 paper comprises Chapters I-VII, the sequel Chapters VIII-IX), in which the authors reassess the error estimates proved in the first part from a probabilistic point of view. The only other copy of either paper listed on ABPC/RBH is the OOC copy of part I (both journal issue and offprint). "Before computers, numerical analysis consisted of stopgap measures for the physical problems that could not be analytically reduced. The resulting hand computations were increasingly aided by mechanical tools which are comparatively well documented, but little was written about numerical algorithms because computing was not considered an archival contribution. "The state of numerical mathematics stayed pretty much the same as Gauss left it until World War II" [Goldstine, The Computer from Pascal to Von Neumann (1972), p. 287]. "Some astronomers and statisticians did computing as part of their research, but few other scientists were numerically oriented. Among mathematicians, numerical analysis had a poor reputation and attracted few specialists" [Aspray, John von Neumann and the Origins of Modern Computing (1999), pp. 49-50]. "As a branch of mathematics, it probably ranked the lowest, even below statistics, in terms of what most university mathematicians found interesting" [Hodges, Alan Turing: the Enigma (1983), p. 316]. "In this environment John von Neumann and Herman Goldstine wrote the first modern paper on numerical analysis, 'Numerical Inverting of Matrices of High Order', and they audaciously published the paper in the journal of record for the American Mathematical Society. The inversion paper was part of von Neumann's efforts to create a mathematical discipline around the new computing machines. Gaussian elimination was chosen to focus the paper, but matrices were not its only subject. The paper was the first to distinguish between the stability of a mathematical problem and of its numerical approximation, to explain the significance in this context of the 'Courant criterium' (later CFL condition), to point out the advantages of.…