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Probing the spectral dimension of quantum network geometries
- Source :
- Digital.CSIC. Repositorio Institucional del CSIC, instname
- Publication Year :
- 2020
- Publisher :
- IOP Publishing, 2020.
-
Abstract
- We consider an environment for an open quantum system described by a 'quantum network geometry with flavor' (QNGF) in which the nodes are coupled quantum oscillators. The geometrical nature of QNGF is reflected in the spectral properties of the Laplacian matrix of the network which display a finite spectral dimension, determining also the frequencies of the normal modes of QNGFs. We show that an a priori unknown spectral dimension can be indirectly estimated by coupling an auxiliary open quantum system to the network and probing the normal mode frequencies in the low frequency regime. We find that the network parameters do not affect the estimate; in this sense it is a property of the network geometry, rather than the values of, e.g., oscillator bare frequencies or the constant coupling strength. Numerical evidence suggests that the estimate is also robust both to small changes in the high frequency cutoff and noisy or missing normal mode frequencies. We propose to couple the auxiliary system to a subset of network nodes with random coupling strengths to reveal and resolve a sufficiently large subset of normal mode frequencies.<br />JN acknowledges funding from the Spanish State Research Agency, through the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R&D (MDM-2017-0711) and thanks Turku Centre for Quantum Physics for the hospitality.
- Subjects :
- Physics - Physics and Society
Network geometry
Computer Networks and Communications
Computer science
media_common.quotation_subject
Quantum physics
FOS: Physical sciences
Physics and Society (physics.soc-ph)
Theoretical physics
Artificial Intelligence
Excellence
Hospitality
Spectral dimension
Agency (sociology)
media_common
Quantum Physics
Quantum network
Simplicial complexes
business.industry
Disordered Systems and Neural Networks (cond-mat.dis-nn)
State (functional analysis)
Condensed Matter - Disordered Systems and Neural Networks
Computer Science Applications
Quantum Physics (quant-ph)
business
Information Systems
Subjects
Details
- ISSN :
- 2632072X
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- Journal of Physics: Complexity
- Accession number :
- edsair.doi.dedup.....5d22dd6f43d75ee94e81b311ff2c0127
- Full Text :
- https://doi.org/10.1088/2632-072x/abaf9b