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Abstract
The Born rule describes the probability of obtaining an outcome when measuring an observable of a quantum system. As it can only be tested by measuring many copies of the system under consideration, it does not hold for non-replicable systems. For these systems, we give a procedure to predict the future statistics of measurement outcomes through Repeated Measurements (RM). This is done by extending the validity of quantum mechanics to those systems admitting no replicas; we prove that if the statistics of the results acquired by performing RM on such systems is sufficiently similar to that obtained by the Born rule, the latter can be used effectively. We apply our framework to a repeatedly measured Unruh-DeWitt detector interacting with a massless scalar quantum field, which is an example of a system (detector) interacting with an uncontrollable environment (field) for which using RM is necessary. Analysing what an observer learns from the RM outcomes, we find a regime where history-dependent RM probabilities are close to the Born ones. Consequently, the latter can be used for all practical purposes. Finally, we numerically study inertial and accelerated detectors, showing that an observer can see the Unruh effect via RM.
| Original language | English |
|---|---|
| Pages (from-to) | 1-31 |
| Number of pages | 31 |
| Journal | Quantum |
| Volume | 8 |
| DOIs | |
| Publication status | Published - 3 Oct 2024 |
| MoE publication type | A1 Journal article-refereed |
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Dive into the research topics of 'Repeated measurements on non-replicable systems and their consequences for Unruh-DeWitt detectors'. Together they form a unique fingerprint.Projects
- 1 Finished
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QTF 2 stage: Finnish Centre of Exellence in Quantum Technology
Pekola, J. (Principal investigator), Satrya, C. (Project Member), Subero Rengel, D. (Project Member), Ankerhold, E. (Project Member), Karimi, B. (Project Member), Lemziakov, S. (Project Member), Chang, Y.-C. (Project Member), Thomas, G. (Project Member) & Marín Suárez, M. (Project Member)
01/05/2020 → 31/12/2022
Project: RCF Centre of Excellence