Book contents
- Frontmatter
- Contents
- Preface
- Acronyms
- 1 Introduction
- 2 Questions and Answers
- 3 Classical Bits
- 4 Quantum Bits
- 5 Classical and Quantum Registers
- 6 Classical Register Mechanics
- 7 Quantum Register Dynamics
- 8 Partial Observations
- 9 Mixed States and POVMs
- 10 Double-Slit Experiments
- 11 Modules
- 12 Computerization and Computer Algebra
- 13 Interferometers
- 14 Quantum Eraser Experiments
- 15 Particle Decays
- 16 Nonlocality
- 17 Bell Inequalities
- 18 Change and Persistence
- 19 Temporal Correlations
- 20 The Franson Experiment
- 21 Self-intervening Networks
- 22 Separability and Entanglement
- 23 Causal Sets
- 24 Oscillators
- 25 Dynamical Theory of Observation
- 26 Conclusions
- Appendix
- References
- Index
7 - Quantum Register Dynamics
Published online by Cambridge University Press: 24 November 2017
- Frontmatter
- Contents
- Preface
- Acronyms
- 1 Introduction
- 2 Questions and Answers
- 3 Classical Bits
- 4 Quantum Bits
- 5 Classical and Quantum Registers
- 6 Classical Register Mechanics
- 7 Quantum Register Dynamics
- 8 Partial Observations
- 9 Mixed States and POVMs
- 10 Double-Slit Experiments
- 11 Modules
- 12 Computerization and Computer Algebra
- 13 Interferometers
- 14 Quantum Eraser Experiments
- 15 Particle Decays
- 16 Nonlocality
- 17 Bell Inequalities
- 18 Change and Persistence
- 19 Temporal Correlations
- 20 The Franson Experiment
- 21 Self-intervening Networks
- 22 Separability and Entanglement
- 23 Causal Sets
- 24 Oscillators
- 25 Dynamical Theory of Observation
- 26 Conclusions
- Appendix
- References
- Index
Summary
Introduction
In this chapter we move beyond the classical register scenario discussed in the previous chapter, extending the discussion to experiments described by timedependent quantum registers of varying rank. We apply our previous discussion of the signal basis representation (SBR), the computational basis representation (CBR), signal operators, signal classes, and the CBR of signal operators to the quantum case. Our discussion of dynamics covers persistence, that is, the stability of apparatus, observers, and laboratory time, and the Born probability rule. We state the principles of quantized detector network (QDN) dynamics and show how they apply to the description of quantum experiments. We discuss the signal theorem and path summations.
Persistence
Our first step is to clarify what QDN assumes about the evolution of apparatus in time, because this affects the modeling. QDN is designed to reflect the behavior of apparatus in the real world and so it is not assumed in general that a given observer's apparatus is constant in time, even during a given run of an experiment.
Although many experiments appear to be carried out with apparatus that persists over any given run of the experiment, and indeed, perhaps over all the runs of that experiment, that is just an incidental factor that reflects no more than an economy in construction. In practice it is invariably easier and more economical to use the same equipment over and over again rather than use it once, throw it away after each run, and build a new version ready for the next run. Lest this be thought of as a trivial point, it is nevertheless an integral and costly feature of many experiments, involving maintenance and upgrading. Indeed, in laboratories such as the Large Hadron Collider, actual run time is a small fraction of total project time. A related, significant issue has to do with the concept of ensemble, discussed in the Appendix.
Persistence has everything to do with time scale, specifically, the relative laboratory time over which any piece of equipment can be meaningfully discussed as such. The degree of persistence of apparatus is as contextual as anything else in physics. If a run is relatively brief, say, over in very small fractions of a second, as in high-energy particle scattering experiments, then in such an experiment, the apparatus will behave as if it persists forever.
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- Quantized Detector NetworksThe Theory of Observation, pp. 84 - 104Publisher: Cambridge University PressPrint publication year: 2017