Recent technological developments have made it increasingly easy to access the non-perturbative regimes of cavity quantum electrodynamics known as ultrastrong or deep strong coupling, where the ...light-matter coupling becomes comparable to the bare modal frequencies. In this work, we address the adequacy of the broadly used single-mode cavity approximation to describe such regimes. We demonstrate that, in the non-perturbative light-matter coupling regimes, the single-mode models become unphysical, allowing for superluminal signalling. Moreover, considering the specific example of the quantum Rabi model, we show that the multi-mode description of the electromagnetic field, necessary to account for light propagation at finite speed, yields physical observables that differ radically from their single-mode counterparts already for moderate values of the coupling. Our multi-mode analysis also reveals phenomena of fundamental interest on the dynamics of the intracavity electric field, where a free photonic wavefront and a bound state of virtual photons are shown to coexist.
We apply deep-neural-network-based techniques to quantum state classification and reconstruction. Our methods demonstrate high classification accuracies and reconstruction fidelities, even in the ...presence of noise and with little data. Using optical quantum states as examples, we first demonstrate how convolutional neural networks (CNNs) can successfully classify several types of states distorted by, e.g., additive Gaussian noise or photon loss. We further show that a CNN trained on noisy inputs can learn to identify the most important regions in the data, which potentially can reduce the cost of tomography by guiding adaptive data collection. Secondly, we demonstrate reconstruction of quantum-state density matrices using neural networks that incorporate quantum-physics knowledge. The knowledge is implemented as custom neural-network layers that convert outputs from standard feed-forward neural networks to valid descriptions of quantum states. Any standard feed-forward neural-network architecture can be adapted for quantum state tomography (QST) with our method. We present further demonstrations of our proposed QST technique with conditional generative adversarial networks (QST-CGAN) Ahmed et al., Phys. Rev. Lett.127, 140502 (2021)10.1103/PhysRevLett.127.140502. We motivate our choice of a learnable loss function within an adversarial framework by demonstrating that the QST-CGAN outperforms, across a range of scenarios, generative networks trained with standard loss functions. For pure states with additive or convolutional Gaussian noise, the QST-CGAN is able to adapt to the noise and reconstruct the underlying state. The QST-CGAN reconstructs states using up to two orders of magnitude fewer iterative steps than iterative and accelerated projected-gradient-based maximum-likelihood estimation (MLE) methods. We also demonstrate that the QST-CGAN can reconstruct both pure and mixed states from two orders of magnitude fewer randomly chosen data points than these MLE methods. Our paper opens possibilities to use state-of-the-art deep-learning methods for quantum state classification and reconstruction under various types of noise.
The interaction of light and matter at the single-photon level is of central importance in various fields of physics, including, e.g., condensed matter physics, astronomy, quantum optics, and quantum ...information. Amplification of such quantum light–matter interaction can be highly beneficial to, e.g., improve device performance, explore novel phenomena, and understand fundamental physics, and has therefore been a long-standing goal. Furthermore, simulation of light–matter interaction in the regime of ultrastrong coupling, where the interaction strength is comparable to the bare frequencies of the uncoupled systems, has also become a hot research topic, and considerable progress has been made both theoretically and experimentally in the past decade. In this review, we provide a detailed introduction of recent advances in amplification of quantum light–matter interaction and simulation of ultrastrong light–matter interaction, particularly in cavity and circuit quantum electrodynamics and in cavity optomechanics.
Amphotericin B (AmB) is a recommended medication for the treatment of cutaneous and mucosal leishmaniasis in cases of therapeutic failure with first-line medications; however, little is known about ...the in vitro susceptibility to AmB of clinical isolates of the subgenus Viannia, which is most prevalent in South America. This work aimed to determine the in vitro susceptibility profiles to AmB of clinical isolates of the species L. (V.) panamensis, L. (V.) guyanensis and L. (V.) braziliensis. In vitro susceptibility to AmB was evaluated for 65 isolates. Macrophages derived from the U937 cell line were infected with promastigotes and exposed to different AmB concentrations. After 96 hours, the number of intracellular amastigotes was quantified by qPCR, and median effective concentration (EC50) was determined using the PROBIT model. The controls included sensitive strains and experimentally derived less sensitive strains generated in vitro, which presented EC50 values up to 7.57-fold higher than the values of the sensitive strains. The isolates were classified into groups according to their in vitro susceptibility profiles using Ward's hierarchical method. The susceptibility to AmB differed in an intraspecies-specific manner as follows: 28.21% (11/39) of L. (V.) panamensis strains, 50% (3/6) of L. (V.) guyanensis strains and 34.61% (9/26) of L. (V.) braziliensis strains were classified as less sensitive. The latter subset featured three susceptibility groups. We identified Colombian isolates with different AmB susceptibility profiles. In addition, the capacity of species of subgenus Viannia to develop lower susceptibility to AmB was demonstrated in vitro. These new findings should be considered in the pharmacovigilance of AmB in Colombia and South America.
Leishmaniasis development is multifactorial; nonetheless, the establishment of the infection, which occurs by the survival and replication of the parasite inside its main host cell, the macrophage, ...is mandatory. Thus, the importance of studying the molecular mechanisms involved in the Leishmania-macrophage interaction is highlighted. The aim of this study was to characterize a cellular model of macrophages derived from U937 cells that would allow for the identification of infection phenotypes induced by genetic silencing with interference RNA in the context of macrophages infected with Leishmania (Viannia) braziliensis. The model was standardized by silencing an exogenous gene (gfp), an endogenous gene (lmna) and a differentially expressed gene between infected and non-infected macrophages (gro-β). The silencing process was successful for the three genes studied, obtaining reductions of 88·9% in the GFP levels, 87·5% in LMNA levels and 74·4% for Gro-β with respect to the corresponding control cell lines. The cell model revealed changes in the infection phenotype of the macrophages in terms of number of amastigotes per infected macrophage, number of amastigotes per sampled macrophage and percentage of infected macrophages as a result of gene silencing. Thus, this cell model constitutes a research platform for the study of parasite-host interactions and for the identification of potentially therapeutic targets.
There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at ...12 months.
A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces.
The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval=0.78-0.83) and the Hedges' g=1.17 (95% confidence interval=1.04-1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit.
The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care.
Different Leishmania species cause distinct clinical manifestations of the infectious disease leishmaniasis. It is fundamentally important to understand the mechanisms governing the interaction ...between Leishmania and its host cell. Little is known about this interaction between Leishmania (Viannia) braziliensis and human macrophages. In this study, we aimed to identify differential gene expression between non-infected and L. (V) braziliensis-infected U937-derived macrophages. We deployed a whole human transcriptome microarray analysis using 72 hours post-infection samples and compared those samples with their non-infected counterparts. We found that 218 genes were differentially expressed between infected and non-infected macrophages. A total of 71.6% of these genes were down-regulated in the infected macrophages. Functional enrichment analyses identified the steroid and sterol/cholesterol biosynthetic processes between regulatory networks down-regulated in infected macrophages. RT-qPCR further confirmed this down-regulation in genes belonging to these pathways. These findings contrast with those from studies involving other Leishmania species at earlier infection stages, where gene up-regulation for this metabolic pathway has been reported. Sterol biosynthesis could be an important biological process associated with the expression profile of macrophages infected by L. (V.) braziliensis. Differential transcriptional results suggest a negative regulation of the genetic regulatory network involved in cholesterol biosynthesis.
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