166 research outputs found
Joint measurement of multiple noncommuting parameters
Although quantum metrology allows us to make precision measurements beyond the standard quantum limit, it mostly works on the measurement of only one observable due to the Heisenberg uncertainty relation on the measurement precision of noncommuting observables for one system. In this paper, we study the schemes of joint measurement of multiple observables which do not commute with each other using the quantum entanglement between two systems. We focus on analyzing the performance of a SU(1,1) nonlinear interferometer on fulfilling the task of joint measurement. The results show that the information encoded in multiple noncommuting observables on an optical field can be simultaneously measured with a signal-to-noise ratio higher than the standard quantum limit, and the ultimate limit of each observable is still the Heisenberg limit. Moreover, we find a resource conservation rule for the joint measurement
Optimum quantum resource distribution for phase measurement and quantum information tapping in a dual-beam SU(1,1) interferometer
Quantum entanglement is a resource in quantum metrology that can be distributed to two conjugate physical quantities for the enhancement of their measurement sensitivity. This is demonstrated in the joint measurement of phase and amplitude modulation signals in quantum dense metrology schemes. We can also devote all the quantum resource to phase measurement only, leading to the optimum sensitivity enhancement. In this paper, we experimentally implement a dual-beam sensing scheme in an SU(1,1) interferometer for the optimum quantum enhancement of phase measurement sensitivity. We demonstrate a 3.9-dB improvement in signal-to-noise ratio over the optimum classical method, and this is 3-dB better than the traditional single-beam scheme. Furthermore, such as cheme also realizes a quantum optical tap of quantum entangled fields and has the full advantages of an SU(1,1) interferometer, such as detection loss tolerance, making it more suitable for practical applications in quantum metrology and quantum information
Versatile and precise quantum state engineering by using nonlinear interferometers
The availability of photon states with well-defined temporal modes is crucial for photonic quantum technologies. Ever since the inception of generating photonic quantum states through pulse pumped spontaneous parametric processes, many exquisite efforts have been put on improving the modal purity of the photon states to achieve single-mode operation. However, because the nonlinear interaction and linear dispersion are often mixed in parametric processes, limited successes have been achieved so far only at some specific wavelengths with sophisticated design. In this paper, we resort to a different approach by exploiting an active filtering mechanism originated from interference fringe of nonlinear interferometer. The nonlinear interferometer is realized in a sequential array of nonlinear medium, with a gap in between made of a linear dispersive medium, in which the precise modal control is realized without influencing the phase matching of the parametric process. As a proof-of-principle demonstration of the capability, we present a photon pairs source using a two-stage nonlinear interferometer formed by two identical nonlinear fibers with a standard single mode fiber in between. The results show that spectrally correlated two-photon state via four wave mixing in a single piece nonlinear fiber is modified into factorable state and heralded single-photons with high modal purity and high heralding efficiency are achievable. This novel quantum interferometric method, which can improve the quality of the photon states in almost all the aspects such as modal purity, heralding efficiency, and flexibility in wavelength selection, is proved to be effective and easy to realize
Building KCNQ1/KCNE1 Channel Models and Probing their Interactions by Molecular-Dynamics Simulations
The slow delayed rectifier (IKs) channel is composed of KCNQ1 (pore-forming) and KCNE1 (auxiliary) subunits, and functions as a repolarization reserve in the human heart. Design of IKs-targeting anti-arrhythmic drugs requires detailed three-dimensional structures of the KCNQ1/KCNE1 complex, a task made possible by Kv channel crystal structures (templates for KCNQ1 homology-modeling) and KCNE1 NMR structures. Our goal was to build KCNQ1/KCNE1 models and extract mechanistic information about their interactions by molecular-dynamics simulations in an explicit lipid/solvent environment. We validated our models by confirming two sets of model-generated predictions that were independent from the spatial restraints used in model-building. Detailed analysis of the molecular-dynamics trajectories revealed previously unrecognized KCNQ1/KCNE1 interactions, whose relevance in IKs channel function was confirmed by voltage-clamp experiments. Our models and analyses suggest three mechanisms by which KCNE1 slows KCNQ1 activation: by promoting S6 bending at the Pro hinge that closes the activation gate; by promoting a downward movement of gating charge on S4; and by establishing a network of electrostatic interactions with KCNQ1 on the extracellular surface that stabilizes the channel in a pre-open activated state. Our data also suggest how KCNE1 may affect the KCNQ1 pore conductance
Loss-tolerant quantum dense metrology with SU(1,1) interferometer
Heisenberg uncertainty relation in quantum mechanics sets the limit on the measurement precision of non-commuting observables in one system, which prevents us from measuring them accurately at the same time. However, quantum entanglement between two systems allows us to infer through Einstein-Podolsky-Rosen correlations two conjugate observables with precision better than what is allowed by Heisenberg uncertainty relation. With the help of the newly developed SU(1,) interferometer, we implement a scheme to jointly measure information encoded in multiple non-commuting observables of an optical field with a signal-to-noise ratio improvement of about 20% over the classical limit on all measured quantities simultaneously. This scheme can be generalized to the joint measurement of information in arbitrary number of non-commuting observables
Combined modeling of cell aggregation and adhesion mediated by receptor–ligand interactions under shear flow
AbstractBlood cell aggregation and adhesion to endothelial cells under shear flow are crucial to many biological processes such as thrombi formation, inflammatory cascade, and tumor metastasis, in which these cellular interactions are mainly mediated by the underlying receptor–ligand bindings. While theoretical modeling of aggregation dynamics and adhesion kinetics of interacting cells have been well studied separately, how to couple these two processes remains unclear. Here we develop a combined model that couples cellular aggregation dynamics and adhesion kinetics under shear flow. The impacts of shear rate (or shear stress) and molecular binding affinity were elucidated. This study provides a unified model where the action of a fluid flow drives cell aggregation and adhesion under the modulations of the mechanical shear flow and receptor–ligand interaction kinetics. It offers an insight into understanding the relevant biological processes and functions
Five Cases Report of Solid Tumor Synchronously with Hematologic Malignancy
The reported incidence of synchronous multiple primary cancer (SMPC) is rare, and it is even less common to observe synchronous solid tumor with a hematological malignancy. We report five cases of solid tumor presented synchronously with hematological malignancy, all observed within a 2 year period at the oncology department of a university hospital in Shanghai, China. These individual cases included lung adenocarcinoma with chronic myelogenous leukemia, colon cancer with solitary plasmocytoma, gastric adenocarcinoma with diffuse large B cell non-Hodgkin's lymphoma, lung adenocarcinoma with multiple myeloma, and colon cancer with diffuse large B cell non-Hodgkin's lymphoma. It is challenging to therapeutically control the biological behavior of concurrent multiple primary tumors, and there is no standard treatment for such rare conditions. In this paper we discuss these five cases of SMPC and their treatments
Defining Essentiality Score of Protein-Coding Genes and Long Noncoding RNAs
Measuring the essentiality of genes is critically important in biology and medicine. Here we proposed a computational method, GIC (Gene Importance Calculator), which can efficiently predict the essentiality of both protein-coding genes and long noncoding RNAs (lncRNAs) based on only sequence information. For identifying the essentiality of protein-coding genes, GIC outperformed well-established computational scores. In an independent mouse lncRNA dataset, GIC also achieved an exciting performance (AUC = 0.918). In contrast, the traditional computational methods are not applicable to lncRNAs. Moreover, we explored several potential applications of GIC score. Firstly, we revealed a correlation between gene GIC score and research hotspots of genes. Moreover, GIC score can be used to evaluate whether a gene in mouse is representative for its homolog in human by dissecting its cross-species difference. This is critical for basic medicine because many basic medical studies are performed in animal models. Finally, we showed that GIC score can be used to identify candidate genes from a transcriptomics study. GIC is freely available at http://www.cuilab.cn/gic/
Chaihu Guizhi Ganjiang Decoction Ameliorates Pancreatic Fibrosis via JNK/mTOR Signaling Pathway
Pancreatic fibrosis is a pathological characteristic of chronic pancreatitis (CP) and pancreatic cancer. Chaihu Guizhi Ganjiang Decoction (CGGD) is a traditional Chinese medicine, which is widely used in the clinical treatment of digestive diseases. However, the potential anti-fibrosis mechanism of CGGD in treating CP remains unclear. Here, we conducted a series of experiments to examine the effect of CGGD on the CP rat model and primary isolated pancreatic stellate cells (PSCs). The results revealed that CGGD attenuated pancreatic damage, decreased collagen deposition, and inhibited PSC activation in the pancreas of CP rats. However, compared with the CP group, CGGD had no effect on body weight and serum amylase and lipase. In addition, CGGD suppressed autophagy by downregulating Atg5, Beclin-1, and LC3B and facilitated phosphorylation of mTOR and JNK in pancreatic tissues and PSCs. Moreover, the CGGD-containing serum also decreased LC3B or collagen I expression after rapamycin (mTOR inhibitor) or SP600125 (JNK inhibitor) treatment in PSCs. In conclusion, CGGD attenuated pancreatic fibrosis and PSC activation, possibly by suppressing autophagy of PSCs through the JNK/mTOR signaling pathway
Quantum Computing for MIMO Beam Selection Problem: Model and Optical Experimental Solution
Massive multiple-input multiple-output (MIMO) has gained widespread
popularity in recent years due to its ability to increase data rates, improve
signal quality, and provide better coverage in challenging environments. In
this paper, we investigate the MIMO beam selection (MBS) problem, which is
proven to be NP-hard and computationally intractable. To deal with this
problem, quantum computing that can provide faster and more efficient solutions
to large-scale combinatorial optimization is considered. MBS is formulated in a
quadratic unbounded binary optimization form and solved with Coherent Ising
Machine (CIM) physical machine. We compare the performance of our solution with
two classic heuristics, simulated annealing and Tabu search. The results
demonstrate an average performance improvement by a factor of 261.23 and 20.6,
respectively, which shows that CIM-based solution performs significantly better
in terms of selecting the optimal subset of beams. This work shows great
promise for practical 5G operation and promotes the application of quantum
computing in solving computationally hard problems in communication.Comment: Accepted by IEEE Globecom 202
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