Quick Navigation
Topics
Quantum Foundations
Non-Markovian Poissonian Spontaneous Collapse Models
arXiv
Authors: Nicolò Piccione
Year
2026
Paper ID
73033
Status
Preprint
Abstract Read
~2 min
Abstract Words
166
Citations
N/A
Abstract
Spontaneous collapse models provide a possible solution to the measurement problem by modifying standard quantum dynamics. The modification consists of adding non-linear and stochastic terms inducing wavefunction collapse in space. Non-Markovian versions of these models are motivated by physical reasons, phenomenological consistency, and potential for relativistic extensions. Here, we investigate a non-Markovian version of the Poissonian Spontaneous Localization (PSL) model, i.e., a model characterized by instantaneous and localized collapse events. We assume that our model is characterized by a typical time scale τC so that, given an initial state ρ0 of standard quantum matter at time t=0, we derive an effective long-time $tgg τC$ statistical dynamics in terms of a CPTP map Φt. We then show how Φt can be made equal to that obtained by non-Markovian CSL models. Moreover, given Φt, we obtain the associated time-convolutionless master equation by means of a supercumulant expansion. Finally, we characterize the collapse events process for events with $t gg τC$ given an initial quantum state ρ0 at t=0.
Why This Paper Matters
- This paper contributes to the Quantum Foundations research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- Spontaneous collapse models provide a possible solution to the measurement problem by modifying standard quantum dynamics.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.