Error-Mitigated Quantum Simulation of Interacting Fermions with Trapped Ions

Quantum error mitigation has been extensively explored to increase the accuracy of the quantum circuits in noisy-intermediate-scale-quantum (NISQ) computation, where quantum error correction requiring additional quantum resources is not adopted. Among various error-mitigation schemes, probabilistic error cancellation (PEC) has been proposed as a general and systematic protocol that can be applied to numerous hardware platforms and quantum algorithms. However, PEC has only been tested in two-qubit systems and a superconducting multi-qubit system by learning a sparse error model. Here, we benchmark PEC using up to four trapped-ion qubits. For the benchmark, we simulate the dynamics of interacting fermions with or without spins by applying multiple Trotter steps. By tomographically reconstructing the error model and incorporating other mitigation methods such as positive probability and symmetry constraints, we are able to increase the fidelity of simulation and faithfully observe the dynamics of the Fermi-Hubbard model, including the different behavior of charge and spin of fermions. Our demonstrations can be an essential step for further extending systematic error-mitigation schemes toward practical quantum advantages.Comment: 15 pages, 11 figure

Real-time Polymerase Chain Reaction

Abstract: The real-time polymerase chain reaction (RT-PCR), also called quantitative real-time polymerase chain reaction (QRT-PCR) or kinetic polymerase chain reaction (kPCR), is a technique used to simultaneously quantify and amplify a DNA molecule. It is used to determine whether a specific DNA sequence is present in the sample; and if it is present, the number of copies in the sample. It is the real-time version of quantitative polymerase chain reaction (qPCR), itself a modification of polymerase chain reaction (PCR). The procedure of RT-PCR follows the regular PCR procedure, but the DNA is quantified after each round of amplification. Two common methods of quantification are the use of fluorescent dyes that intercalate with double-strand DNA, and modified DNA oligonucleotide probes that fluoresce when hybridized with a complementary DNA. RT-PCR could be combined with reverse transcription polymerase chain reaction to quantify messenger RNA (mRNA) at a particular time for in a particular cell or tissue type

Scalable and Programmable Phononic Network with Trapped Ions

Controllable bosonic systems can provide post-classical computational power with sub-universal quantum computational capability. A network that consists of a number of bosons evolving through beam-splitters and phase-shifters between different modes, has been proposed and applied to demonstrate quantum advantages. While the network has been implemented mostly in optical systems with photons, recently alternative realizations have been explored, where major limitations in photonic systems such as photon loss, and probabilistic manipulation can be addressed. Phonons, the quantized excitations of vibrational modes, of trapped ions can be a promising candidate to realize the bosonic network. Here, we experimentally demonstrate a minimal-loss phononic network that can be programmed and in which any phononic states are deterministically prepared and detected. We realize the network with up to four collective-vibrational modes, which can be straightforwardly extended to reveal quantum advantage. We benchmark the performance of the network with an exemplary algorithm of tomography for arbitrary multi-mode states with a fixed total phonon number. We obtain reconstruction fidelities of 94.5 $\pm$ 1.95 % and 93.4 $\pm$ 3.15 % for single-phonon and two-phonon states, respectively. Our experiment demonstrates a clear and novel pathway to scale up a phononic network for various quantum information processing beyond the limitations of classical and other quantum systems

Regulated internalization of NMDA receptors drives PKD1-mediated suppression of the activity of residual cell-surface NMDA receptors

Background Constitutive and regulated internalization of cell surface proteins has been extensively investigated. The regulated internalization has been characterized as a principal mechanism for removing cell-surface receptors from the plasma membrane, and signaling to downstream targets of receptors. However, so far it is still not known whether the functional properties of remaining (non-internalized) receptor/channels may be regulated by internalization of the same class of receptor/channels. The N-methyl-D-aspartate receptor (NMDAR) is a principal subtype of glutamate-gated ion channel and plays key roles in neuronal plasticity and memory functions. NMDARs are well-known to undergo two types of regulated internalization – homologous and heterologous, which can be induced by high NMDA/glycine and DHPG, respectively. In the present work, we investigated effects of regulated NMDAR internalization on the activity of residual cell-surface NMDARs and neuronal functions. Results In electrophysiological experiments we discovered that the regulated internalization of NMDARs not only reduced the number of cell surface NMDARs but also caused an inhibition of the activity of remaining (non-internalized) surface NMDARs. In biochemical experiments we identified that this functional inhibition of remaining surface NMDARs was mediated by increased serine phosphorylation of surface NMDARs, resulting from the activation of protein kinase D1 (PKD1). Knockdown of PKD1 did not affect NMDAR internalization but prevented the phosphorylation and inhibition of remaining surface NMDARs and NMDAR-mediated synaptic functions. Conclusion These data demonstrate a novel concept that regulated internalization of cell surface NMDARs not only reduces the number of NMDARs on the cell surface but also causes an inhibition of the activity of remaining surface NMDARs through intracellular signaling pathway(s). Furthermore, modulating the activity of remaining surface receptors may be an effective approach for treating receptor internalization-induced changes in neuronal functions of the CNS

Plasma lipid profiles and homocysteine levels in anti-N-methyl-D-aspartate receptor encephalitis

IntroductionWe aimed to investigate whether lipid profiles and homocysteine levels in patients with anti-N-methyl-D-aspartate receptor encephalitis are related to clinical presentation and prognosis, which may contribute to further research on the pathogenesis and treatment of this disease.MethodsThis study included a total of 43 patients with anti-N-methyl-D-aspartate receptor encephalitis and 43 sex–age-matched healthy controls. Baseline demography, clinical data, patient outcomes, and ancillary examination results were recorded. Patients were followed up every 2–3 months during the first year. The modified Rankin Scale score was used to evaluate the therapeutic effect and clinical outcome.ResultsAmong the 43 patients included in this study, 55.81% were male, the mean age of onset was 27 years old, and the median modified Rankin Scale score on admission was 3.0. Apolipoprotein A-1 was significantly lower in patients with anti-N-methyl-D-aspartate receptor encephalitis compared with healthy controls (p = 0.004). Compared with healthy controls, homocysteine (p = 0.002), apolipoprotein B (p = 0.004), Lpa (p = 0.045), and apolipoprotein B/apolipoprotein A-1 (p = 0.001) were significantly increased in patients with anti-N-methyl-D-aspartate receptor encephalitis. According to the modified Rankin Scale scores, 6 months after discharge, 72.09% of patients had a good prognosis and 27.91% had a poor prognosis. In the good prognosis group, age (p = 0.031), lipoprotein a (p = 0.023), apolipoprotein A-1 (p = 0.027) at baseline, and the modified Rankin Scale score on admission (p = 0.019) were significantly higher than those in the poor prognosis group.ConclusionThis study suggests the possibility that serum lipid profile and homocysteine play an important role in the pathogenesis of anti-N-methyl-D-aspartate receptor encephalitis, providing support for lipid-lowering treatment of anti-N-methyl-D-aspartate receptor encephalitis patients

Employing a novel bioelastomer to toughen polylactide

Biodegradable, biocompatible polylactide (PLA) synthesized from renewable resources has attracted extensive interests over the past decades and holds great potential to replace many petroleum-derived plastics. With no loss of biodegradability and biocompatibility, we highly toughened PLA using a novel bioelastomer (BE)–synthesized from biomass diols and diacids. Although PLA and BE are immiscible, BE particles of ∼1 μm in diameter are uniformly dispersed in the matrix, and this indicates some compatibility between PLA and BE. BE significantly increased the cold crystallization ability of PLA, which was valuable for practical processing and performance. SEM micrographs of fracture surface showed a brittle-to-ductile transition owing to addition of BE. At 11.5 vol%, notched Izod impact strength improved from 2.4 to 10.3 kJ/m2, 330% increment; the increase is superior to previous toughening effect by using petroleum-based tougheners

Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture

© 2020, The Author(s). Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD