Beating the break-even point with a discrete-variable-encoded logical qubit.

Quantum error correction (QEC) aims to protect logical qubits from noises by using the redundancy of a large Hilbert space, which allows errors to be detected and corrected in real time1. In most QEC codes2-8, a logical qubit is encoded in some discrete variables, for example photon numbers, so that the encoded quantum information can be unambiguously extracted after processing. Over the past decade, repetitive QEC has been demonstrated with various discrete-variable-encoded scenarios9-17. However, extending the lifetimes of thus-encoded logical qubits beyond the best available physical qubit still remains elusive, which represents a break-even point for judging the practical usefulness of QEC. Here we demonstrate a QEC procedure in a circuit quantum electrodynamics architecture18, where the logical qubit is binomially encoded in photon-number states of a microwave cavity8, dispersively coupled to an auxiliary superconducting qubit. By applying a pulse featuring a tailored frequency comb to the auxiliary qubit, we can repetitively extract the error syndrome with high fidelity and perform error correction with feedback control accordingly, thereby exceeding the break-even point by about 16% lifetime enhancement. Our work illustrates the potential of hardware-efficient discrete-variable encodings for fault-tolerant quantum computation19.

Study on the Dynamic Changes in Non-Volatile Metabolites of Rizhao Green Tea Based on Metabolomics.

The processing of tea leaves plays a crucial role in the formation of the taste of the resulting tea. In order to study the compositions of and changes in taste-related substances during the processing of Rizhao green tea, non-targeted metabolomics was used, based on UHPLC-Q Exactive MS. Totals of 529, 349, and 206 non-volatile metabolites were identified using three different detection modes, of which 112 secondary metabolites were significantly changed. Significant variations in secondary metabolites were observed during processing, especially during the drying stage, and the conversion intensity levels of non-volatile metabolites were consistent with the law of "Drying > Fixation > Rolling". The DOT method was used to screen tea-quality-related compounds that contributed significantly to the taste of Rizhao green tea, including (-)-epicatechin gallate, (-)-epicatechin gallate, gallic acid, L-theanine, and L-leucine, which make important contributions to taste profiles, such as umami and bitterness. Metabolic pathway analysis revealed that purine metabolism, caffeine metabolism, and tyrosine metabolism perform key roles in the processing of Rizhao green tea in different processing stages. The results of this study provide a theoretical basis for tea processing and practical advice for the food industry.

Observation of Topological Magnon Insulator States in a Superconducting Circuit.

Searching topological states in artificial systems has recently become a rapidly growing field of research. Meanwhile, significant experimental progress on observing topological phenomena has been made in superconducting circuits. However, topological insulator states have not yet been reported in this system. Here, for the first time, we experimentally realize a tunable dimerized spin chain model and observe the topological magnon insulator states in a superconducting qubit chain. Via parametric modulations of the qubit frequencies, we show that the qubit chain can be flexibly tuned into topologically trivial or nontrivial magnon insulator states. Based on monitoring the quantum dynamics of a single-qubit excitation in the chain, we not only measure the topological winding numbers, but also observe the topological magnon edge and defect states. Our experiment exhibits the great potential of tunable superconducting qubit chain as a versatile platform for exploring noninteracting and interacting symmetry-protected topological states.

Coulomb Oscillations in a Gate-Controlled Few-Layer Graphene Quantum Dot.

Graphene quantum dots could be an ideal host for spin qubits and thus have been extensively investigated based on graphene nanoribbons and etched nanostructures; however, edge and substrate-induced disorders severely limit device functionality. Here, we report the confinement of quantum dots in few-layer graphene with tunable barriers, defined by local strain and electrostatic gating. Transport measurements unambiguously reveal that confinement barriers are formed by inducing a band gap via the electrostatic gating together with local strain induced constriction. Numerical simulations according to the local top-gate geometry confirm the band gap opening by a perpendicular electric field. We investigate the magnetic field dependence of the energy-level spectra in these graphene quantum dots. Experimental results reveal a complex evolution of Coulomb oscillations with the magnetic field, featuring kinks at level crossings. The simulation of energy spectrum shows that the kink features and the magnetic field dependence are consistent with experimental observations, implying the hybridized nature of energy-level spectrum of these graphene quantum dots.

Experimental Quantum Randomness Processing Using Superconducting Qubits.

Coherently manipulating multipartite quantum correlations leads to remarkable advantages in quantum information processing. A fundamental question is whether such quantum advantages persist only by exploiting multipartite correlations, such as entanglement. Recently, Dale, Jennings, and Rudolph negated the question by showing that a randomness processing, quantum Bernoulli factory, using quantum coherence, is strictly more powerful than the one with classical mechanics. In this Letter, focusing on the same scenario, we propose a theoretical protocol that is classically impossible but can be implemented solely using quantum coherence without entanglement. We demonstrate the protocol by exploiting the high-fidelity quantum state preparation and measurement with a superconducting qubit in the circuit quantum electrodynamics architecture and a nearly quantum-limited parametric amplifier. Our experiment shows the advantage of using quantum coherence of a single qubit for information processing even when multipartite correlation is not present.

[Traditional Chinese medicine inheritance system analysis of professor Ding Yuanqing in treating tic disorder medication based on experience].

In recent years, the incidence of tic disorders has increased, and it is not uncommon for the patients to treat the disease. The pathogenesis and pathogenesis of Western medicine are not yet clear, the clinical commonly used western medicine has many adverse reactions, traditional Chinese medicine (TCM) research is increasingly valued. Based on the software of TCM inheritance assistant system, this paper discusses Ding Yuanqing's experience in treating tic disorder with Professor. Collect yuan Qing Ding professor in treating tic disorder of medical records by association rules Apriori algorithm, complex system entropy clustering without supervision and data mining method, carries on the analysis to the selected 800 prescriptions, to determine the frequency of use of prescription drugs, the association rules between the drug and digging out the 12 core combination and the first six new prescription, medication transferred to the liver and extinguish wind, cooling blood and relieving convulsion, Qingxin soothe the nerves, with the card cut, flexible application, strict compatibility.

The regularity of nourishing-yin prescription for treating ascites due to hepatitis B cirrhosis based on data mining technology.

Background: Clinically, Chinese medicine is mostly used to treat ascites due to hepatitis B cirrhosis by nourishing-yin. We summarize the pattern of prescriptions for nourishing-yin inascites due to hepatitis B cirrhosis based on data mining to better use traditional Chinese medicine (TCM) to treat cirrhotic ascites in hepatitis B. Methods: Articles published from 2000 to 2020 on ascites due to hepatitis B cirrhosis were searched in the Chinese National Knowledge Infrastructure and Chinese Science and Technology Journal Database. The results of the search were screened and then treated as the data sources in turn. Based on the data sources, a prescription database of ascites due to hepatitis B cirrhosis was constructed. The data mining was conducted by statistical analysis of frequency and association. Core herbs, including the property and flavor, channel tropism, regularities of medicinal recipes, and core sets, among others, were examined. Results: Through combing 199 articles, a total of 201 prescriptions were selected, involving 138 kinds of herbs. The efficacy of cold herbs was slightly higher than that of warm herbs. The main flavors of herbs were sweet, bitter, and pungent. There were 30 herbs used ≥26 times in 201 prescriptions. The highest frequency of use was Poria cocos, followed by atractylodis macrocephalae, and radix astragali. Ninety-nine commonly used drug combinations were obtained according to the association rules, of which there were 60 associated drug groups with a frequency ≥34, of which the highest frequency was poria cocos-rhizoma atractylodis macrocephalae, poria cocos-oriental water plantain rhizome, poria cocos-radix astragali. Frequent medicinal recipes consisted largely of medicines for tonifying deficiency, including diuretics for eliminating dampness, medicines for promoting blood circulation and removing blood stasis, and supplements for clearing heat and regulating qi. Conclusions: Through data mining, it was found that when TCM treats ascites due to hepatitis B cirrhosis, it attaches importance to using methods of tonifying deficiency and invigorating spleen for diuresis based on nourishing-yin to improve the clinical efficacy, which can provide reference for TCM's clinical use of nourishing-yin to treat ascites due to hepatitis B cirrhosis.

Deep quantum neural networks on a superconducting processor.

Deep learning and quantum computing have achieved dramatic progresses in recent years. The interplay between these two fast-growing fields gives rise to a new research frontier of quantum machine learning. In this work, we report an experimental demonstration of training deep quantum neural networks via the backpropagation algorithm with a six-qubit programmable superconducting processor. We experimentally perform the forward process of the backpropagation algorithm and classically simulate the backward process. In particular, we show that three-layer deep quantum neural networks can be trained efficiently to learn two-qubit quantum channels with a mean fidelity up to 96.0% and the ground state energy of molecular hydrogen with an accuracy up to 93.3% compared to the theoretical value. In addition, six-layer deep quantum neural networks can be trained in a similar fashion to achieve a mean fidelity up to 94.8% for learning single-qubit quantum channels. Our experimental results indicate that the number of coherent qubits required to maintain does not scale with the depth of the deep quantum neural network, thus providing a valuable guide for quantum machine learning applications with both near-term and future quantum devices.

A flying Schrödinger's cat in multipartite entangled states.

Schrödinger's cat originates from the famous thought experiment querying the counterintuitive quantum superposition of macroscopic objects. As a natural extension, several "cats" (quasi-classical objects) can be prepared into coherent quantum superposition states, which is known as multipartite cat states demonstrating quantum entanglement among macroscopically distinct objects. Here, we present a highly scalable approach to deterministically create flying multipartite Schrödinger's cat states by reflecting coherent-state photons from a microwave cavity containing a superconducting qubit. We perform full quantum state tomography on the cat states with up to four photonic modes and confirm the existence of quantum entanglement among them. We also witness the hybrid entanglement between discrete-variable states (the qubit) and continuous-variable states (the flying multipartite cat) through a joint quantum state tomography. Our work provides an enabling step for implementing a series of quantum metrology and quantum information processing protocols based on cat states.

An ultra-high gain single-photon transistor in the microwave regime.

A photonic transistor that can switch or amplify an optical signal with a single gate photon requires strong non-linear interaction at the single-photon level. Circuit quantum electrodynamics provides great flexibility to generate such an interaction, and thus could serve as an effective platform to realize a high-performance single-photon transistor. Here we demonstrate such a photonic transistor in the microwave regime. Our device consists of two microwave cavities dispersively coupled to a superconducting qubit. A single gate photon imprints a phase shift on the qubit state through one cavity, and further shifts the resonance frequency of the other cavity. In this way, we realize a gain of the transistor up to 53.4 dB, with an extinction ratio better than 20 dB. Our device outperforms previous devices in the optical regime by several orders in terms of optical gain, which indicates a great potential for application in the field of microwave quantum photonics and quantum information processing.

One-pot fabrication of lignin-based aromatic porous polymers for efficient removal of bisphenol AF from water.

To remove the bisphenol AF (BPAF) from aqueous solution, two different types of lignin-based aromatic porous polymers (LAPP-1 and LAPP-2) were fabricated via one-pot crosslinking of lignin with 1,4-dichloroxylene and 4,4'-bis(chloromethyl)-1,1'-biphenyl, respectively. The successful synthesis of LAPPs was confirmed by FTIR and XPS, SEM, TEM and N2 adsorption-desorption analysis. Then, batch adsorption experiments were conducted to investigate adsorption properties toward BPAF. Based on the results, the adsorption processes were in accordance with the pseudo-second-order kinetic model and the Freundlich isotherm model, and the thermodynamic studies showed that the adsorption was a spontaneous and exothermic process. It is remarkable that LAPPs exhibited good adsorption performance in wide ranges of pH and ionic strength as well as in recycling process. Notably, compared to LAPP-1, LAPP-2 exhibited higher adsorption capacity for BPAF, which can be ascribed to its higher porosity and content of aromatic ring. Moreover, the comprehensive analysis of experimental and theoretical results indicated that the π-π interactions and pore adsorption may jointly drive the uptake process of BPAF. Considering the simple fabrication method employed and excellent BPAF adsorption performance, LAPPs provided new insights into the development of advanced lignin-based adsorbents for removal of BPAF from water.

Immunohistochemical Analysis of CYP11B2, CYP11B1 and ß-catenin Helps Subtyping and Relates With Clinical Characteristics of Unilateral Primary Aldosteronism.

Background: Primary aldosteronism is caused by aldosterone overproduction. While conventional hematoxylin-eosin staining can demonstrate morphological abnormality, it cannot provide any functional histopathological information. We aimed to identify the diagnostic, functional and prognostic value of CYP11B2, CYP11B1, and ß-catenin immunostaining in unilateral hyperaldosteronism. Method: A total of 134 patients with unilateral hyperaldosteronism were recruited in our study. The expression of CYP11B2, CYP11B1, and ß-catenin was evaluated semiquantitatively on 134 patients' sections using immunohistochemistry technology and the relationship with clinical data was assessed. Results: Patients were classified into four subtypes based on CYP11B2 staining as below: (1)118 patients with unilateral single aldosterone-producing adenoma (APA), (2)11 with unilateral multiple APA, (3)four with aldosterone-producing cell cluster (APCC), and (4)one with an undefined source. Adjusted CYP11B2 H-score was correlated with serum aldosterone, aldosterone to renin ratio (ARR), and serum potassium. In the abnormal ß-catenin staining group, hypertension duration, aldosterone, ARR, cortisol, tumor diameter, tumor area, and CYP11B2 H-score were significantly higher than those of the wild-type group. Serum potassium level was significantly lower in the abnormal ß-catenin staining group. Age, gender, BMI, family history of hypertension, adjusted CYP11B2 and CYP11B1 H-scores differed significantly between complete clinical success and incomplete clinical success groups. Age, gender and family history of hypertension were independently associated with complete clinical success based on multivariate logistic regression analysis. Conclusion: CYP11B2 immunostaining could improve the differential diagnosis of unilateral hyperaldosteronism. Adjusted CYP11B2 H-score could be used as a histopathological marker to reflect the severity of unilateral APA. Dysregulation of Wnt/ß-catenin signaling and impaired ß-catenin degradation may provoke the proliferation and enhance the steroidogenic ability of APA tumor cells, indicating that the Wnt pathway might be a potential, actionable, therapeutic target in the treatment of hyperaldosteronism. Age, sex and family history of hypertension were independent predictors of clinical outcome after adrenalectomy for unilateral hyperaldosteronism.

Influence of Body Mass Index on Survival and Prognosis in Squamous Cell Carcinoma of Head and Neck.

OBJECTIVE: Differences in body mass index (BMI) were used to analyze the survival and prognosis of SCCHN patients. PATIENTS AND METHODS: A retrospective cohort study was conducted to select 323 patients who underwent surgical treatment for SCCHN from June 2013 to June 2016. The patients were divided into a healthy BMI group (BMI<24kg/m2), an overweight group (24kg/m2≤BMI<28kg/m2) and an obese group (BMI≥28 kg/m2). Various statistical methods were used to summarize and analyze clinical data, complications, disease specific survival (DSS), the overall survival (OS), and recurrence-free survival (RFS) within the last 3 y. RESULTS: At 3 y, OS (54.40%) and DSS (51.94%) were slightly lower in the obese group compared with the overweight (64.62%, 61.92%) and healthy BMI groups (64.66%, 65.02%), but no statistical significance was found in DSS (P=0.178), OS (P=0.123) and RFS (P=0.362). The difference in operation duration (P=0.008) and bleeding volume (P=0.001) in obese patients was consistent with those in diabetes mellitus (P=0.002) and coronary heart disease (P=0.000). A high incidence of pharyngeal fistula was observed in obese (P=0.014) and overweight patients (P=0.025), but mouth floor fistula (P=0.038), lung infection (P=0.047), fat liquefaction (P=0.003) and lower extremities deep venous thrombosis (P=0.020) were only found in the obese group. Cox univariatable and multivariatable analysis showed that clinical stage, T stage, and N stage were independent prognostic factors for patients with SCCHN, which was not related to BMI. CONCLUSION: BMI was associated with a higher probability of complications. However, BMI had no significant correlation with 3-year OS, RFS and DSS, and was not a prognostic indicator for patients with SCCHN.

Comparison of a twice daily injection of insulin aspart 50 with insulin aspart 30 in patients with poorly controlled type 2 diabetes.

OBJECTIVE: To compare the efficacy and safety of a twice daily injection of insulin aspart (BIAsp) 30 and BIAsp50 in patients with type 2 diabetes mellitus (T2DM) poorly controlled with oral hypoglycemic agents (OHAs). METHODS: In this 12 week prospective, randomized, parallel trial, a total of 80 T2DM patients, 59 ± 10 years old with a disease duration of 9.3 ± 6.6 years and HbA1c >7% despite large doses of metformin and sulfonylurea administration, were randomized to receive BIAsp30 (n = 40) or BIAsp50 (n = 40). The primary endpoint was a change in HbA1c at week 12. RESULTS: The changes in HbA1c from baseline were -2.5% ± 1.0% in the BIAsp50 group and -2.5% ± 1.2% in the BIAsp30 group (p = .897). No difference was observed in the rate of HbA1c target achievement (<7.0%) between BIAsp50 (42.5%) and BIAsp30 (32.5%) (p = .495). The change in fasting plasma glucose (FPG) in the BIAsp50 group was lower than that in the BIAsp30 group (p < .001), while the change in two-hour postprandial blood glucose (2hPBG) was higher and blood glucose excursion was lower in the BIAsp50 group than that in the BIAsp30 group (p < .001, p < .001). A significant improvement in HbA1c was observed with BIAsp50 in subgroups with baseline blood glucose excursion >7.8 mmol/L or 2hPBG >17.6 mmol/L compared with BIAsp30. There were no differences in hypoglycemia or body weight between groups. CONCLUSIONS: Compared with BIAsp30, BIAsp50 showed greater efficacy in patients with baseline BG excursion >7.8 mmol/L or 2hPBG >17.6 mmol/L as well as good safety for hypoglycemia. CLINICAL TRIAL REGISTRATION: ChiCTR-IIR-16008958.

Quantum generative adversarial learning in a superconducting quantum circuit.

Generative adversarial learning is one of the most exciting recent breakthroughs in machine learning. It has shown splendid performance in a variety of challenging tasks such as image and video generation. More recently, a quantum version of generative adversarial learning has been theoretically proposed and shown to have the potential of exhibiting an exponential advantage over its classical counterpart. Here, we report the first proof-of-principle experimental demonstration of quantum generative adversarial learning in a superconducting quantum circuit. We demonstrate that, after several rounds of adversarial learning, a quantum-state generator can be trained to replicate the statistics of the quantum data output from a quantum channel simulator, with a high fidelity (98.8% on average) so that the discriminator cannot distinguish between the true and the generated data. Our results pave the way for experimentally exploring the intriguing long-sought-after quantum advantages in machine learning tasks with noisy intermediate-scale quantum devices.

Self-Assembled and Self-Monitored Sorafenib/Indocyanine Green Nanodrug with Synergistic Antitumor Activity Mediated by Hyperthermia and Reactive Oxygen Species-Induced Apoptosis.

Liver cancer is a leading cause of cancer morbidity and mortality worldwide, especially in China. Sorafenib (SRF) is currently the most commonly used systemic agent against advanced hepatocellular carcinoma (HCC), which is the most common type of liver cancer. However, HCC patients have only limited benefit and suffer a serious side effect from SRF. Therefore, new approaches are urgently needed to improve the therapeutic effectiveness of SRF and reduce its side effect. In our current study, we developed a self-imaging and self-delivered nanodrug with SRF and indocyanine (ICG) to improve the therapeutic effect of sorafenib against HCC. With the π-π stacking effect between SRF and ICG, a one-step nanoprecipitation method was designed to obtain the SRF/ICG nanoparticles (SINP) via self-assembly. Pluronic F127 was used to shield the SINP to further improve the stability in an aqueous environment. The stability, photothermal effect, cell uptake, ROS production, cytotoxicity, tumor imaging, and tumor-targeting and tumor-killing efficacy of the SINP were evaluated in vitro and in vivo by using an HCC cell line Huh7 and its xenograft tumor model. We found that our designed SINP showed monodisperse stability and efficient photothermal effect both in vitro and in vivo. SINP could rapidly enter Huh7 cells and achieve potent cytotoxicity under near-infrared (NIR) laser irradiation partly by producing a great amount of reactive oxygen species (ROS). SINP had significantly improved stability and blood half-life, and could specifically target tumor via the enhanced permeability and retention (EPR) effect in vivo. In addition, SINP showed improved cytotoxicity in both subcutaneous and orthotopic HCC implantation models in vivo. Overall, this rationally designed sorafenib delivery system with a very high loading capacity (33%) has considerably improved antitumor efficiency in vitro and could completely eliminate subcutaneous tumors without any regrowth in vivo. In conclusion, our self-imaging and self-delivered nanodrug could improve the efficacy of SRF and might be a potential therapy for HCC patients.

Experimental repetitive quantum channel simulation.

Universal control of quantum systems is a major goal to be achieved for quantum information processing, which demands thorough understanding of fundamental quantum mechanics and promises applications of quantum technologies. So far, most studies concentrate on ideally isolated quantum systems governed by unitary evolutions, while practical quantum systems are open and described by quantum channels due to their inevitable coupling to environment. Here, we experimentally simulate arbitrary quantum channels for an open quantum system, i.e. a single photonic qubit in a superconducting quantum circuit. The arbitrary channel simulation is achieved with minimum resource of only one ancilla qubit and measurement-based adaptive control. By repetitively implementing the quantum channel simulation, we realize an arbitrary Liouvillian for a continuous evolution of an open quantum system for the first time. Our experiment provides not only a testbed for understanding quantum noise and decoherence, but also a powerful tool for full control of practical open quantum systems.

Simulation of molecular spectroscopy with circuit quantum electrodynamics.

Spectroscopy is a crucial laboratory technique for understanding quantum systems through their interactions with the electromagnetic radiation. Particularly, spectroscopy is capable of revealing the physical structure of molecules, leading to the development of the maser-the forerunner of the laser. However, real-world applications of molecular spectroscopy are mostly confined to equilibrium states, due to computational and technological constraints; a potential breakthrough can be achieved by utilizing the emerging technology of quantum simulation. Here we experimentally demonstrate through a toy model, a superconducting quantum simulator capable of generating molecular spectra for both equilibrium and non-equilibrium states, reliably producing the vibronic structure of diatomic molecules. Furthermore, our quantum simulator is applicable not only to molecules with a wide range of electronic-vibronic coupling strength, characterized by the Huang-Rhys parameter, but also to molecular spectra not readily accessible under normal laboratory conditions. These results point to a new direction for predicting and understanding molecular spectroscopy, exploiting the power of quantum simulation.

Specific On-site Assembly of Multifunctional Magnetic Nanocargos Based on Highly Efficient and Parallelized Bioconjugation: Toward Personalized Cancer Targeting Therapy.

The rational design of particle-based cancer theranostic agents, combining diagnostic and therapeutic features in a single entity, has emerged as an effective approach toward personalized cancer therapy; however, creating a flexible assembly of specific targeting ligands with regard to a broad range of tumor tissues and cells is still challenging. Here, we present a convenient and highly variable on-site assembly strategy for the preparation of multifunctional doxorubicin (DOX)-loaded nanocargos with magnetic supraparticles (MSPs) as a core and redox-degradable poly(methylacrylic acid-co-N,N-bis(acryloyl) cystamine) (P(MAA-co-Cy) as the shell, which could be simultaneously modified with multiple targeting ligands through parallelized bioconjugation on the basis of a streptavidin-biotin (SA-BT) interaction. Under physiological conditions similar to those of the cytoplasm of tumor cells, DOX could be released in a controlled manner from these nanocargos to specific tumor sites, while dual-ligand modified nanocargos showed remarkable proliferation inhibition for the HeLa cells and the SK-OV-3 cells that overexpressed both folate as well as integrin receptors. The experimental results demonstrated that the on-site assembly strategy described herein opens access to highly efficient targeting drug delivery systems toward personalized cancer targeting therapy by incorporating functional diversity, which can be easily achieved through highly efficient and parallelized one-step bioconjugation.