Error-mitigated Quantum Approximate Optimization via Learning-based Adaptive Optimization

Combinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum computing is envisioned as a powerful tool offering potential computational advantages for solving some of these problems. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical hybrid algorithms, is designed to solve certain combinatorial optimization problems by transforming a discrete optimization problem into a classical optimization problem over a continuous circuit parameter domain. QAOA objective landscape over the parameter variables is notorious for pervasive local minima and barren plateaus, and its viability in training significantly relies on the efficacy of the classical optimization algorithm. To enhance the performance of QAOA, we design double adaptive-region Bayesian optimization (DARBO), an adaptive classical optimizer for QAOA. Our experimental results demonstrate that the algorithm greatly outperforms conventional gradient-based and gradient-free optimizers in terms of speed, accuracy, and stability. We also address the issues of measurement efficiency and the suppression of quantum noise by successfully conducting the full optimization loop on the superconducting quantum processor. This work helps to unlock the full power of QAOA and paves the way toward achieving quantum advantage in practical classical tasks.Comment: Main text: 11 pages, 4 figures, SI: 5 pages, 5 figure

Impact of Opinions and Relationships Coevolving on Self-Organization of Opinion Clusters

In a social network, individual opinions and interpersonal relationships always interact and coevolve. This continuously leads to self-organization of opinion clusters in the whole network. In this article we study how the coevolution on the two kinds of complex networks and the self-organization of opinion clusters are differently affected by the dynamic parameters, the structural parameters and the propagating parameters. It is found that the two dynamic parameters are homogeneous bringing about the strong and weak relations, while the two structural parameters are heterogeneous having equivalent relations. Moreover, the impact of the propagating parameter has been found only above its threshold

The transport properties of Kekul\'e-ordered graphene pp-nn junctions

The transport properties of electrons in graphene $p$-$n$ junction with uniform Kekul\'e lattice distortion have been studied using the tight-binding model and the Landauer-B\"uttiker formalism combined with the nonequilibrium Green's function method. In the Kekul\'e-ordered graphene, the original $K$ and $K^{\prime}$ valleys of the pristine graphene are folded together due to the $\sqrt{3} \times \sqrt{3}$ enlargement of the primitive cell. When the valley coupling breaks the chiral symmetry, special transport properties of Dirac electrons exist in the Kekul\'e lattice. In the O-shaped Kekul\'e graphene $p$-$n$ junction, Klein tunneling is suppressed, and only resonance tunneling occurs. In the Y-shaped Kekul\'e graphene $p$-$n$ junction, the transport of electrons is dominated by Klein tunneling. When the on-site energy modification is introduced into the Y-shaped Kekul\'e structure, both Klein tunneling and resonance tunneling occur, and the electron tunneling is enhanced. In the presence of a strong magnetic field, the conductance of O-shaped and on-site energy-modified Y-shaped Kekul\'e graphene $p$-$n$ junctions is non-zero due to the occurrence of resonance tunneling. It is also found that the disorder can enhance conductance, with conductance plateaus forming in the appropriate range of disorder strength. The ideal plateau value is found only in the Kekul\'e-Y system.Comment: 8 pages, 7 figure

Optimized sample preparation for two-dimensional gel electrophoresis of soluble proteins from chicken bursa of Fabricius

<p>Abstract</p> <p>Background</p> <p>Two-dimensional gel electrophoresis (2-DE) is a powerful method to study protein expression and function in living organisms and diseases. This technique, however, has not been applied to avian bursa of Fabricius (BF), a central immune organ. Here, optimized 2-DE sample preparation methodologies were constructed for the chicken BF tissue. Using the optimized protocol, we performed further 2-DE analysis on a soluble protein extract from the BF of chickens infected with virulent avibirnavirus. To demonstrate the quality of the extracted proteins, several differentially expressed protein spots selected were cut from 2-DE gels and identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).</p> <p>Results</p> <p>An extraction buffer containing 7 M urea, 2 M thiourea, 2% (w/v) 3-[(3-cholamidopropyl)-dimethylammonio]-1-propanesulfonate (CHAPS), 50 mM dithiothreitol (DTT), 0.2% Bio-Lyte 3/10, 1 mM phenylmethylsulfonyl fluoride (PMSF), 20 U/ml Deoxyribonuclease I (DNase I), and 0.25 mg/ml Ribonuclease A (RNase A), combined with sonication and vortex, yielded the best 2-DE data. Relative to non-frozen immobilized pH gradient (IPG) strips, frozen IPG strips did not result in significant changes in the 2-DE patterns after isoelectric focusing (IEF). When the optimized protocol was used to analyze the spleen and thymus, as well as avibirnavirus-infected bursa, high quality 2-DE protein expression profiles were obtained. 2-DE maps of BF of chickens infected with virulent avibirnavirus were visibly different and many differentially expressed proteins were found.</p> <p>Conclusion</p> <p>These results showed that method C, in concert extraction buffer IV, was the most favorable for preparing samples for IEF and subsequent protein separation and yielded the best quality 2-DE patterns. The optimized protocol is a useful sample preparation method for comparative proteomics analysis of chicken BF tissues.</p

Super-multiplex vibrational imaging

The ability to visualize directly a large number of distinct molecular species inside cells is increasingly essential for understanding complex systems and processes. Even though existing methods have successfully been used to explore structure–function relationships in nervous systems, to profile RNA in situ, to reveal the heterogeneity of tumour microenvironments and to study dynamic macromolecular assembly, it remains challenging to image many species with high selectivity and sensitivity under biological conditions. For instance, fluorescence microscopy faces a ‘colour barrier’, owing to the intrinsically broad (about 1,500 inverse centimetres) and featureless nature of fluorescence spectra that limits the number of resolvable colours to two to five (or seven to nine if using complicated instrumentation and analysis). Spontaneous Raman microscopy probes vibrational transitions with much narrower resonances (peak width of about 10 inverse centimetres) and so does not suffer from this problem, but weak signals make many bio-imaging applications impossible. Although surface-enhanced Raman scattering offers high sensitivity and multiplicity, it cannot be readily used to image specific molecular targets quantitatively inside live cells. Here we use stimulated Raman scattering under electronic pre-resonance conditions to image target molecules inside living cells with very high vibrational selectivity and sensitivity (down to 250 nanomolar with a time constant of 1 millisecond). We create a palette of triple-bond-conjugated near-infrared dyes that each displays a single peak in the cell-silent Raman spectral window; when combined with available fluorescent probes, this palette provides 24 resolvable colours, with the potential for further expansion. Proof-of-principle experiments on neuronal co-cultures and brain tissues reveal cell-type-dependent heterogeneities in DNA and protein metabolism under physiological and pathological conditions, underscoring the potential of this 24-colour (super-multiplex) optical imaging approach for elucidating intricate interactions in complex biological systems

Synthesis, biological evaluation and mechanism studies of C-23 modified 23-hydroxybetulinic acid derivatives as anticancer agents

A series of C-23 modified 23-hydroxybetulinic acid (HBA) derivatives were synthesized and evaluated for their antiproliferative activity against a panel of cancer cell lines (A2780, A375, B16, MCF-7 and HepG2). The biological screening results showed that most of the derivatives exhibited more potent antiproliferative activity than HBA, and compound 6e exhibited the most potent activity with IC50 values of 2.14 μM, 2.89 μM, and 3.97 μM against A2780, B16, and MCF-7 cells, respectively. Further anticancer mechanism studies revealed that compound 6e induced the generation of intracellular reactive oxygen species (ROS) and reduction of mitochondrial membrane potential (MMP) of B16 cells in a dose-dependent manner. Moreover, western blot analysis indicated that compound 6e downregulated the expression of anti-apoptotic protein Bcl-2 and upregulated the expression of proapoptotic protein Bax, activation of caspase 3 to induce cell apoptosis. Meanwhile, compound 6e significantly inhibited the phosphorylation of MEK, ERK, and Akt without affecting the expression of MEK, ERK, and Akt. Furthermore, the in vivo anti-tumor activity of 6e was validated (tumor inhibitory ratio of 68.4% at the dose of 30 mg/kg) in mice with B16 melanoma

A map of human cancer signaling

We conducted a comprehensive analysis of a manually curated human signaling network containing 1634 nodes and 5089 signaling regulatory relations by integrating cancer-associated genetically and epigenetically altered genes. We find that cancer mutated genes are enriched in positive signaling regulatory loops, whereas the cancer-associated methylated genes are enriched in negative signaling regulatory loops. We further characterized an overall picture of the cancer-signaling architectural and functional organization. From the network, we extracted an oncogene-signaling map, which contains 326 nodes, 892 links and the interconnections of mutated and methylated genes. The map can be decomposed into 12 topological regions or oncogene-signaling blocks, including a few ‘oncogene-signaling-dependent blocks' in which frequently used oncogene-signaling events are enriched. One such block, in which the genes are highly mutated and methylated, appears in most tumors and thus plays a central role in cancer signaling. Functional collaborations between two oncogene-signaling-dependent blocks occur in most tumors, although breast and lung tumors exhibit more complex collaborative patterns between multiple blocks than other cancer types. Benchmarking two data sets derived from systematic screening of mutations in tumors further reinforced our findings that, although the mutations are tremendously diverse and complex at the gene level, clear patterns of oncogene-signaling collaborations emerge recurrently at the network level. Finally, the mutated genes in the network could be used to discover novel cancer-associated genes and biomarkers

Experimental study on shear performance of RC beams strengthened with NSM CFRP prestressed concrete prisms

This paper presents an experimental investigation of the shear performance of RC beams strengthened with near surface mounted (NSM) carbon fibre reinforced polymer (CFRP) prestressed concrete prisms (PCPs). The shear behaviour of strengthened beams can be affected by several design variables. In this research, the effect of the following parameters were considered: the prestress level, inclination and spacing of the CFRP-PCPs, and material type of the prism. The control beam had conventional shear steel reinforcement only while the other seven beams were shear strengthened with CFRP-PCPs by varying design parameters mentioned above. All the beams were tested under monotonic loading until they reached the failure load. The experimental results showed that the NSM CFRP-PCPs strengthening technique improves the shear performance of the beams effectively. The strengthened beams that applied the CFRP-PCPs at an inclination of 45 • were more efficient in improving the shear capacity compared to vertical CFRP-PCPs. The shear capacity and deformation were enhanced with the increase of prestressing levels of CFRP rods and the decrease of CFRP-PCPs spacing. The failure modes of the strengthened beams were influenced mainly by the spacing and the inclination of the CFRP-PCPs. Moreover, the material type of the prism had little influence on the effectiveness of shear strengthening. The analytical model presented was developed to estimate the shear contribution of NSM CFRP-PCPs and the model was found to predict the shear capacity of the tested beams well