scholarly journals Observing the Spectral Collapse of Two-Photon Interaction Models

Proceedings ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 41
Author(s):  
Simone Felicetti ◽  
Alexandre Boité

Until very recently, two-photon interaction processes have been considered only as arising from second- or higher-order effects in driven systems, and so limited to extremely small coupling strengths. However, a variety of novel physical phenomena emerges in the strong and ultrastrong coupling regimes. Strikingly, for a critical value of the coupling strength the discrete spectrum collapses into a continuous band. In this extended abstract, we discuss recent proposals to implement genuine two-photon interactions in an undriven solid-state system, in the framework of circuit QED. In particular, we review counterintuitive spectral features of two-photon interaction models and we show how the onset of the spectral collapse can be observed in feasible scattering experiments.

2018 ◽  
Vol 15 (12) ◽  
pp. 125204
Author(s):  
Haiming Yuan ◽  
Chunfeng Wu ◽  
Decun Li ◽  
Mei Li ◽  
Xun-Li Feng ◽  
...  

1992 ◽  
Vol 70 (5) ◽  
pp. 379-382
Author(s):  
A. M. Abdel-Hafez

We investigate the phenomena of single-mode and two-mode squeezing for a three-level atom and two modes. The field modes are initially taken in coherent states. The effects of detuning on these phenomena are studied for one-photon and two-photon interactions. The relation between the collapse and revival phenomena and single-mode and two-mode squeezing is shown. It is found that the two-mode squeezing is much more effective than the single-mode squeezing for the one-photon interaction. While for the two-photon interaction the reverse is true.


2019 ◽  
Author(s):  
Joe Butler ◽  
Samuel Ngabo ◽  
Marcus Missal

Complex biological systems build up temporal expectations to facilitate adaptive responses to environmental events, in order to minimise costs associated with incorrect responses, and maximise the benefits of correct responses. In the lab, this is clearly demonstrated in tasks which show faster response times when the period between warning (S1) and target stimulus (S2) on the previous trial was short and slower when the previous trial foreperiod was long. The mechanisms driving such higher order effects in temporal preparation paradigms are still under debate, with key theories proposing that either i) the foreperiod leads to automatic modulation of the arousal system which influences responses on the subsequent trial, or ii) that exposure to a foreperiod results in the creation of a memory trace which is used to guide responses on the subsequent trial. Here we provide data which extends the evidence base for the memory accounts, by showing that previous foreperiod exposures are cumulative with reaction times shortening after repeated exposures; whilst also demonstrate that the higher order effects associated with a foreperiod remain active for several trials.


AI and Ethics ◽  
2021 ◽  
Author(s):  
Marc Steen ◽  
Tjerk Timan ◽  
Ibo van de Poel

AbstractThe collection and use of personal data on citizens in the design and deployment of algorithms in the domain of justice and security is a sensitive topic. Values like fairness, autonomy, privacy, accuracy, transparency and property are at stake. Negative examples of algorithms that propagate or exacerbate biases, inequalities or injustices have received ample attention, both in academia and in popular media. To supplement this view, we will discuss two positive examples of Responsible Innovation (RI): the design and deployment of algorithms in decision support, with good intentions and careful approaches. We then explore potential, unintended, undesirable, higher-order effects of algorithms—effects that may occur despite good intentions and careful approaches. We do that by engaging with anticipation and responsiveness, two key dimensions of Responsible Innovation. We close the paper with proposing a framework and a series of tentative recommendations to promote anticipation and responsiveness in the design and deployment of algorithms in decision support in the domain of justice and security.


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