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Quantum Measurement

Braginsky, Vladimir B., Khalili, Farid Ya, Thorne, Kip S.·1992·Cambridge University Press eBooks

Abstract

This book is an up-to-date introduction to the quantum theory of measurement, a fast developing field of intense current interest to scientists and engineers for its potential high technology applications. It is also a subject of importance to students for its central role in the foundations of quantum mechanics. Although the main principles of the field were elaborated in the 1930s by Bohr, Schrödinger, Heisenberg, von Neumann and Mandelstam, it was not until the 1980s that technology became sufficiently advanced to allow its application in real experiments. Quantum measurement is now central to many ultra-high technology developments, such as squeezed light, single atom traps, and searches for gravitational radiation. It is also considered to have great promise for computer science and engineering, particularly for its applications in information processing and transfer. The book contains a pedagogical introduction to the relevant theory written at a level accessible to those with only a modest background in quantum mechanics. It then goes on to discuss aspects of the design of practical quantum measurement systems. This book is essential reading for all scientists and engineers interested in the potential applications of technology near the quantum limit. It will also serve as an ideal supplement to standard quantum mechanics textbooks at the advanced undergraduate or graduate level.

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Metadata

Authors
Braginsky, V. B., Khalili, F. Y., & Thorne, K. S.
Venue
Cambridge University Press eBooks
Published
1992-09-24
OpenAlex
W2912981457
Cited by
820
References
0
FWCI
4.90
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Quantum Measurement. https://app.cochat.ai/papers/10.1017/cbo9780511622748
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Braginsky, V. B., Khalili, F. Y., & Thorne, K. S. (1992). Quantum Measurement. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511622748

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.