Mapping photonic entanglement into and out of a quantum memory

Recent developments of quantum information science critically rely on entanglement, an intriguing aspect of quantum mechanics where parts of a composite system can exhibit correlations stronger than any classical counterpart. In particular, scalable quantum networks require capabilities to create, store, and distribute entanglement among distant matter nodes via photonic channels. Atomic ensembles can play the role of such nodes. So far, in the photon counting regime, heralded entanglement between atomic ensembles has been successfully demonstrated via probabilistic protocols. However, an inherent drawback of this approach is the compromise between the amount of entanglement and its preparation probability, leading intrinsically to low count rate for high entanglement. Here we report a protocol where entanglement between two atomic ensembles is created by coherent mapping of an entangled state of light. By splitting a single-photon and subsequent state transfer, we separate the generation of entanglement and its storage. After a programmable delay, the stored entanglement is mapped back into photonic modes with overall efficiency of 17 %. Improvements of single-photon sources together with our protocol will enable "on demand" entanglement of atomic ensembles, a powerful resource for quantum networking.Comment: 7 pages, and 3 figure

Long-distance quantum communication with atomic ensembles and linear optics

Quantum communication holds a promise for absolutely secure transmission of secret messages and faithful transfer of unknown quantum states. Photonic channels appear to be very attractive for physical implementation of quantum communication. However, due to losses and decoherence in the channel, the communication fidelity decreases exponentially with the channel length. We describe a scheme that allows to implement robust quantum communication over long lossy channels. The scheme involves laser manipulation of atomic ensembles, beam splitters, and single-photon detectors with moderate efficiencies, and therefore well fits the status of the current experimental technology. We show that the communication efficiency scale polynomially with the channel length thereby facilitating scalability to very long distances.Comment: 2 tex files (Main text + Supplement), 4 figure

Quantum simulation of the wavefunction to probe frustrated Heisenberg spin systems

Quantum simulators are controllable quantum systems that can reproduce the dynamics of the system of interest, which are unfeasible for classical computers. Recent developments in quantum technology enable the precise control of individual quantum particles as required for studying complex quantum systems. Particularly, quantum simulators capable of simulating frustrated Heisenberg spin systems provide platforms for understanding exotic matter such as high-temperature superconductors. Here we report the analog quantum simulation of the ground-state wavefunction to probe arbitrary Heisenberg-type interactions among four spin-1/2 particles . Depending on the interaction strength, frustration within the system emerges such that the ground state evolves from a localized to a resonating valence-bond state. This spin-1/2 tetramer is created using the polarization states of four photons. The single-particle addressability and tunable measurement-induced interactions provide us insights into entanglement dynamics among individual particles. We directly extract ground-state energies and pair-wise quantum correlations to observe the monogamy of entanglement

The Quantum Internet

Quantum networks offer a unifying set of opportunities and challenges across exciting intellectual and technical frontiers, including for quantum computation, communication, and metrology. The realization of quantum networks composed of many nodes and channels requires new scientific capabilities for the generation and characterization of quantum coherence and entanglement. Fundamental to this endeavor are quantum interconnects that convert quantum states from one physical system to those of another in a reversible fashion. Such quantum connectivity for networks can be achieved by optical interactions of single photons and atoms, thereby enabling entanglement distribution and quantum teleportation between nodes.Comment: 15 pages, 6 figures Higher resolution versions of the figures can be downloaded from the following link: http://www.its.caltech.edu/~hjkimble/QNet-figures-high-resolutio

Obesity management and continuing medical education in primary care: results of a Swiss survey

ABSTRACT: BACKGROUND: The worldwide increase in obesity is becoming a major health concern. General practitioners (GPs) play a central role in managing obesity. We aimed to examine Swiss GPs self-reported practice in diagnosis and treatment of obesity with a special focus on the performance of waist measurement.. METHODS: A structured self-reported questionnaire was mailed to 323 GPs recruited from four urban physician networks in Switzerland. Measures included professional experience, type of practice, obesity-related continuing medical education (CME) and practice in dealing with obesity such as waist measurement. We assessed the association between the performance of waist measurement and obesity-related CME by multivariate ordered logistic regression controlling for GP characteristics as potential confounders. RESULTS: A total of 187 GPs responded to the questionnaire. More than half of the GPs felt confident in managing obesity. The majority of the GPs (73%) spent less than 4 days in the last 5 years on obesity-related CME. More than half of GPs gave advice to reduce energy intakes (64%), intakes of high caloric and alcoholic drinks (56%) and to increase the physical activity (78%). Half of the GPs seldom performed waist measurement and documentation. The frequency of obesity-related CME was independently associated with the performance of waist measurement when controlled for GPs' characteristics by multivariate ordered logistic regression. CONCLUSIONS: The majority of GPs followed guideline recommendations promoting physical activity and dietary counselling. We observed a gap between the increasing evidence for waist circumference assessment as an important measure in obesity management and actual clinical practice. Our data indicated that specific obesity-related CME might help to reduce this gap

Profiling of the Tetraspanin CD151 Web and Conspiracy of CD151/Integrin β1 Complex in the Progression of Hepatocellular Carcinoma

Tetraspanin CD151 has been implicated in metastasis through forming complexes with different molecular partners. In this study, we mapped tetraspanin web proteins centered on CD151, in order to explore the role of CD151 complexes in the progression of hepatocellular carcinoma (HCC). Immunoprecipitation was used to isolate tetraspanin complexes from HCCLM3 cells using a CD151 antibody, and associated proteins were identified by mass spectrometry. The interaction of CD151 and its molecular partners, and their roles in invasiveness and metastasis of HCC cells were assayed through disruption of the CD151 network. Finally, the clinical implication of CD151 complexes in HCC patients was also examined. In this study, we identified 58 proteins, characterized the tetraspanin CD151 web, and chose integrin β1 as a main partner to further investigate. When the CD151/integrin β1 complex in HCC cells was disrupted, migration, invasiveness, secretion of matrix metalloproteinase 9, and metastasis were markedly influenced. However, both CD151 and integrin β1 expression were untouched. HCC patients with high expression of CD151/integrin β1 complex had the poorest prognosis of the whole cohort of patients. Together, our data show that CD151 acts as an important player in the progression of HCC in an integrin β1-dependent manner

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

Selective Hyper-responsiveness of the Interferon System in Major Depressive Disorders and Depression Induced by Interferon Therapy

Though an important percentage of patients with chronic hepatitis C virus (HCV) undergoing interferon (IFN) therapy develop depressive symptoms, the role of the IFN system in the pathogenesis of depressive disorders is not well understood.50 patients with HCV infection were treated with standard combination therapy (pegylated IFN-α2a/ribavirin). IFN-induced gene expression was analyzed to identify genes which are differentially regulated in patients with or without IFN-induced depression. For validation, PBMC from 22 psychiatric patients with a severe depressive episode (SDE) and 11 controls were cultivated in vitro with pegylated IFN-α2a and gene expression was analyzed.IFN-induced depression in HCV patients was associated with selective upregulation of 15 genes, including 6 genes that were previously described to be relevant for major depressive disorders or neuronal development. In addition, increased endogenous IFN-production and selective hyper-responsiveness of these genes to IFN stimulation were observed in SDE patients.Our data suggest that selective hyper-responsiveness to exogenous (IFN therapy) or endogenous (depressive disorders) type I IFNs may lead to the development of depressive symptoms. These data could lead to the discovery of novel therapeutic approaches to treat IFN-induced and major depressive disorders