Masterpieces of Italian Violin Making 1620-1850: Twenty-Six Important Stringed Instruments from the Collection at the Royal Academy of Music

Chapter 7 illustrates the results obtained by applying the Schrödinger equation to a simple pedagogical quantum system, the particle in a one-dimensional box. The wave functions are seen to be sine waves; their wavelengths are evaluated and used to calculate the quantized energies via the de Broglie relation. An energy-level diagram of some of the energies is constructed; on it are illustrations of the corresponding wave functions and probability distributions. The wave functions are seen to be either symmetric or antisymmetric about the midpoint of the line representing the box, thereby providing a lead-in to the later exploration of certain symmetry properties of multi-electron atoms. It is next pointed out that the Schrödinger equation for this system is identical to Newton’s equation describing the vibrations of a stretched musical string. The different meaning of the two solutions is discussed, as is the concept and structure of linear superpositions of them.

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The role of the Royal Academy of Engineering

Engineering Management ◽

10.1049/em:19940404 ◽

1994 ◽

Vol 4 (4) ◽

pp. 173

Author(s):

S.W. Barlow

Keyword(s):

Royal Academy

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Abstracts of communications to the section of biological sciences, royal academy of medicine in ireland

Irish Journal of Medical Science (1971 -) ◽

10.1007/bf02947198 ◽

1963 ◽

Vol 38 (4) ◽

pp. 185-186

Author(s):

I. C. Roddie ◽

J. V. McLoughlin

Keyword(s):

Biological Sciences ◽

Royal Academy

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A data-driven approach to violin making

Scientific Reports ◽

10.1038/s41598-021-88931-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sebastian Gonzalez ◽

Davide Salvi ◽

Daniel Baeza ◽

Fabio Antonacci ◽

Augusto Sarti

Keyword(s):

Statistical Learning ◽

Geometric Parameters ◽

Data Driven ◽

Vibrational Properties ◽

Learning Tools ◽

Predictive Tool ◽

Complete Control ◽

Data Driven Approach ◽

To Come ◽

Violin Making

AbstractOf all the characteristics of a violin, those that concern its shape are probably the most important ones, as the violin maker has complete control over them. Contemporary violin making, however, is still based more on tradition than understanding, and a definitive scientific study of the specific relations that exist between shape and vibrational properties is yet to come and sorely missed. In this article, using standard statistical learning tools, we show that the modal frequencies of violin tops can, in fact, be predicted from geometric parameters, and that artificial intelligence can be successfully applied to traditional violin making. We also study how modal frequencies vary with the thicknesses of the plate (a process often referred to as plate tuning) and discuss the complexity of this dependency. Finally, we propose a predictive tool for plate tuning, which takes into account material and geometric parameters.

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