Validating quantum-supremacy experiments with exact and fast tensor network contraction

The quantum circuits that declare quantum supremacy, such as Google Sycamore [Nature \textbf{574}, 505 (2019)], raises a paradox in building reliable result references. While simulation on traditional computers seems the sole way to provide reliable verification, the required run time is doomed with an exponentially-increasing compute complexity. To find a way to validate current ``quantum-supremacy" circuits with more than $50$ qubits, we propose a simulation method that exploits the ``classical advantage" (the inherent ``store-and-compute" operation mode of von Neumann machines) of current supercomputers, and computes uncorrelated amplitudes of a random quantum circuit with an optimal reuse of the intermediate results and a minimal memory overhead throughout the process. Such a reuse strategy reduces the original linear scaling of the total compute cost against the number of amplitudes to a sublinear pattern, with greater reduction for more amplitudes. Based on a well-optimized implementation of this method on a new-generation Sunway supercomputer, we directly verify Sycamore by computing three million exact amplitudes for the experimentally generated bitstrings, obtaining an XEB fidelity of $0.191\%$ which closely matches the estimated value of $0.224\%$. Our computation scales up to $41,932,800$ cores with a sustained single-precision performance of $84.8$ Pflops, which is accomplished within $8.5$ days. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems as well as combinatorial optimization problems where one often needs to contract many tensor networks which share a significant portion of tensors in common.Comment: 7 pages, 4 figures, comments are welcome

Expressions and Clinical Significances of TSLC1 and 4.1B in Non-small Cell Lung Cancer

Background and objective Tumor suppressor in lung cancer-1 (TSLC1) belongs to immunoglobulin superfamily of cell adhesion molecule and differentially expressed in adenocarcinoma of the lung (4.1B)belongs to NF2/ERM/4.1 protein superfamily. They may suppress carcinogenesis via construction of the adjacent cell adhesion stability. The aim of this study is to detect the expressions of TSLC1 and 4.1B in non-small cell lung cancer and the clinical pathological significances. Methods The expressions of TSLC1 and 4.1B were detected by RT-PCR in 52 cases of non-small cell lung cancer and corresponding adjacent cancer lung tissues. Results The expressions of TSLC1 and 4.1B in cancer tissues were significantly lower than that in adjacent cancer lung tissues (0.349±0.008 vs 0.555±0.010; 0.209±0.040 vs 0.721±0.071) (P < 0.01). The expressions of TSLC1 and 4.1B showed a significant correlation with cancer differentiation and TNM staging (P < 0.05), but not with gender, age and pathological type (P > 0.05). The expressions of TSLC1 and 4.1B were positively correlated (r=0.471, P < 0.001). Conclusion Down-regulated expressions of TSLC1 and 4.1B in non-small cell lung cancer, both may participate in a cascade of non-small cell lung cancer occurrence and development. TSLC1 and 4.1B are promising targets for non-small cell lung cancer diagnosis and treatment

Preparation and Thermoelectric Properties Study of Bipyridine-Containing Polyfluorene Derivative/SWCNT Composites

Polymer/inorganic thermoelectric composites have witnessed rapid progress in recent years, but most of the studies have focused on the traditional conducting polymers. The limited structures of traditional conducting polymers restrain the development of organic thermoelectric composites. Herein, we report the preparation and thermoelectric properties of a series of composites films based on SWCNTs and bipyridine-containing polyfluorene derivatives. The value of the power factor around 12 μW m−1 K−2 was achieved for the composite F8bpy/SWCNTs with a mass ratio of 50/50, and the maximum value of 62.3 μW m−1 K−2 was obtained when the mass ratio reached 10/90. Moreover, taking advantage of the bipyridine unit could chelate various kinds of metal ions to form polymer complexes. The enhanced power factor of 87.3 μW m−1 K−2 was obtained for composite F8bpy-Ni/SWCNTs with a mass ratio of 50/50. Finally, the thermoelectric properties of the bipyridine-containing polyfluorene derivative/SWCNT composites were conveniently tuned by chelating with different metal ions

High-time resolution PM2.5 source apportionment assisted by spectrum-based characteristics analysis

Characteristics extraction and anomaly analysis based on frequency spectrum can provide crucial support for source apportionment of PM2.5 pollution. In this study, an effective source apportionment framework combining the Fast Fourier Transform (FFT)- and Continuous Wavelet Transform (CWT)-based spectral analyses and Positive Matrix Factorization (PMF) receptor model is developed for spectrum characteristics extraction and source contribution assessment. The developed framework is applied to Beijing during the winter heating period with 1-h time resolution. The spectrum characteristics of anomaly frequency, location, duration and intensity of PM2.5 pollution can be captured to gain an in-depth understanding of source-oriented information and provide necessary indicators for reliable PMF source apportionment. The combined analysis demonstrates that the secondary inorganic aerosols make relatively high contributions (50.59 %) to PM2.5 pollution during the winter heating period in Beijing, followed by biomass burning, vehicle emission, coal combustion, road dust, industrial process and firework emission sources accounting for 15.01 %, 11.00 %, 10.70 %, 5.31 %, 3.88 %, and 3.51 %, respectively. The source apportionment result suggests that combining frequency spectrum characteristics with source apportionment can provide consistent rationales for understanding the temporal evolution of PM2.5 pollution, identifying the potential source types and quantifying the related contributions.ISSN:0048-9697ISSN:1879-102

Lifetime-based Optimization for Simulating Quantum Circuits on a New Sunway Supercomputer

High-performance classical simulator for quantum circuits, in particular the tensor network contraction algorithm, has become an important tool for the validation of noisy quantum computing. In order to address the memory limitations, the slicing technique is used to reduce the tensor dimensions, but it could also lead to additional computation overhead that greatly slows down the overall performance. This paper proposes novel lifetime-based methods to reduce the slicing overhead and improve the computing efficiency, including, an interpretation method to deal with slicing overhead, an inplace slicing strategy to find the smallest slicing set and an adaptive tensor network contraction path refiner customized for Sunway architecture. Experiments show that in most cases the slicing overhead with our inplace slicing strategy would be less than the Cotengra , which is the most used graph path optimization software at present. Finally, the resulting simulation time is reduced to 89.1s for the Sycamore quantum processor RQC, with a sustainable single-precision performance of 308.6Pflops using over 41M cores to generate 1M correlated samples, which is more than 5 times performance improvement compared to 60.4 Pflops in 2021 Gordon Bell Prize work.Comment: 11 pages, 12 figure

A comparative study of the nanopore structure characteristics of coals and Longmaxi shales in China

Both of the coalbed methane (CBM) and shale gas reservoirs are dominated by nanometer-scale pores with their nanopore structures controlling the occurrence, enrichment, and accumulation of natural gas. Low-pressure nitrogen gas adsorption (LP-N(2)GA), low-pressure carbon dioxide gas adsorption (LP-CO(2)GA), high-pressure methane adsorption (HPMA), and field emission scanning electron microscope (FE-SEM) experiments were conducted on 14 different-rank coal samples and nine Longmaxi shale samples collected from various basins in China to compare their nanopore characteristics. The FE-SEM results indicate that the pore structures of both the coal and shale samples consist of nanometer-sized pores that primarily developed in the organic matter. The types of their isothermal adsorption curves are similar. However, the coal and shale samples possess various hysteresis loops, which suggest that the nanopores in shale are open-plated, whereas those in coal are semi-open. Furthermore, the specific surface area (SSA) and pore volume (PV) of the micropores in coal are much larger than those of the mesopores, with the micropore SSAs accounting for 99% of the total SSA in the coal samples. However, the micropore SSAs in the shale samples only account 42.24% of the total SSA. These different nanopore structures reflect their different methane adsorption mechanisms. The methane adsorption of coal is primarily controlled by the micropore SSA, whereas that of shale is primarily controlled by the mesopore SSA. If we use mesopore SSA to analyze its impact on methane adsorption capacity of coal and shale, it will be mismatched. However, no mismatching relationship exists between the total SSAs and adsorption capacities of coal and shale. This study highlights the controlling effect of total SSA on methane adsorption capacity