Connecting Quantum Contextuality and Genuine Multipartite Nonlocality with the Quantumness Witness

The Clauser Horne--Shimony-Holt-type noncontextuality inequality and the Svetliehny inequality are derived from the Alicki-van Ryn quantumness witness. Thus connections between quantumness and quantum contextuality, and between quantumness and genuine multipartite nonlocality are established.

Detecting Quantumness in the n-cycle Exclusivity Graphs

Quantum contextuality is one kind of quantumness that distinguishes quantum mechanics from classical theory.As the simplest exclusivity graph,quantum contextuality of the n-cycle graph has been reviewed,while only for odd n the quantumness can be revealed.Motivated by this,we propose the degree of non-commutativity and the degree of uncertainty to measure the quantumness in the n-cycle graphs.As desired,these two measures can detect the quantumness of any n-cycle graph when n≥4.

Quantifying the quantumness of ensembles via unitary similarity invariant norms

The quantification of the quantumness of a quantum ensemble has theoretical and practical signif- icance in quantum information theory. We propose herein a class of measures of the quantumness of quantum ensembles using the unitary similarity invariant norms of the commutators of the con- stituent density operators of an ensemble. Rigorous proof shows that they share desirable properties for a measure of quantumness, such as positivity, unitary invariance, concavity under probabilistic union, convexity under state decomposition, decreasing under coarse graining, and increasing under fine graining. Several specific examples illustrate the applications of these measures of quantumness in studying quantum information.

Exploring Nanoscale Perovskite Materials for Next‑Generation Photodetectors:A Comprehensive Review and Future Directions

The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis routes.This review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and nanocrystals.Through a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread implementation.In addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection systems.This review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.

Study of thermal decoherence of harmonic oscillators

The thermal decoherence of harmonic oscillators is investigated here.The quantum system presented here is a one-dimensional oscillator with angular frequency,which is surrounded by a thermal bath of environmental oscillators.There are various environmental oscillators with different angular frequency(below an ultraviolet cutoff).At the beginning,the quantum system is a pure state and the environmental oscillators are in thermodynamic equilibrium with temperature.After a period,the system-environment interactions inspire significant decoherence of the quantum state.Such decoherence is displayed by explicit calculations of the purity and von Neumann entropy of the quantum system.It is worth noting that the decoherence could be significant even in the weak coupling and low temperature case due to the large amount of environmental degrees of freedom.Since the decoherence process is inspired between the quantum system and an ordinary thermal environment here,the thermal decoherence result is quite general.

Negativity of Quantumness and Non-Markovianity in a Qubit Coupled to a Thermal Ising Spin Bath System

We propose a scheme to characterize the non-Markovian dynamics and quantify the non-Markovianity via the non-classicality measured by the negativity of quantumness. By considering a qubit in contact with a critical Ising spin bath and introducing an ancilla, we show that revivals of negativity of quantumness indicate the non-Markovian dynamics.Furthermore, a normalized measure of non-Markovianity based on the negativity of quantumness is introduced and the influences of bath criticality, bath temperature and bath size on the non-Markovianity are discussed. It is shown that,at the critical point, the decay of non-Markovianity versus the size of spin bath is the fastest and the non-Markovianity is exactly zero only in the thermodynamic limit. Besides, non-trivial behaviours of negativity of quantumness such as sudden change, double sudden changes and keeping constant are found for different relations between parameters of the initial state. Finally, how the non-classicality of the system is affected by a series of bang-bang pulses is also examined.

Quantumness protection for open systems in a double-layer environment

We study the dynamics of two-level atomic systems(qubits) subject to a double-layer environment that consists of a network of single-mode cavities coupled to a common reservoir. A general exact master equation for the dynamics of a qubit system can be obtained by the quantum-state-diffusion(QSD) approach, which is extended to our spin-cavity-boson model. The quantumness of the atoms comprising coherence and entanglement is investigated for various configurations of the double-layer environment.The findings indicate that parametric control is available for the preservation and generation of system-quantumness by regulating the cavity network. Moreover the underlying physics is profoundly revealed by an effective model obtained by a unitary transformation. Therefore, our work provides an interesting proposal to protect the quantumness of open systems in the framework of a double-layer environment containing bosonic modes.

基于开源Quantum ESPRESSO软件的固体物理教学模式创新与实践

为了解决固体物理课程学习中的难点,授课时引入开源Quantum ESPRESSO软件为学生提供全面的理论学习和实践训练。实践训练分为理论学习和实际操作两个阶段,使学生在理解固体物理的难点的同时获得实际操作经验。通过自主学习、实验报告的撰写和实操演示等分层次的学习方式,学生逐渐提升对固体物理的整体理解水平。学生对这一学习方式的反应良好。Quantum ESPRESSO软件为学生提供了先进的学习工具,有效提高了固体物理课程的学习效果。

Understanding Bridging Sites and Accelerating Quantum Efficiency for Photocatalytic CO_(2) Reduction

We report a novel double-shelled nanoboxes photocatalyst architecture with tailored interfaces that accelerate quantum efficiency for photocatalytic CO_(2) reduction reaction(CO_(2)RR)via Mo–S bridging bonds sites in S_(v)–In_(2)S_(3)@2H–MoTe_(2).The X-ray absorption near-edge structure shows that the formation of S_(v)–In_(2)S_(3)@2H–MoTe_(2) adjusts the coordination environment via interface engineering and forms Mo–S polarized sites at the interface.The interfacial dynamics and catalytic behavior are clearly revealed by ultrafast femtosecond transient absorption,time-resolved,and in situ diffuse reflectance–Infrared Fourier transform spectroscopy.A tunable electronic structure through steric interaction of Mo–S bridging bonds induces a 1.7-fold enhancement in S_(v)–In_(2)S_(3)@2H–MoTe_(2)(5)photogenerated carrier concentration relative to pristine S_(v)–In_(2)S_(3).Benefiting from lower carrier transport activation energy,an internal quantum efficiency of 94.01%at 380 nm was used for photocatalytic CO_(2)RR.This study proposes a new strategy to design photocatalyst through bridging sites to adjust the selectivity of photocatalytic CO_(2)RR.

Quafu-RL:The cloud quantum computers based quantum reinforcement learning

With the rapid advancement of quantum computing,hybrid quantum–classical machine learning has shown numerous potential applications at the current stage,with expectations of being achievable in the noisy intermediate-scale quantum(NISQ)era.Quantum reinforcement learning,as an indispensable study,has recently demonstrated its ability to solve standard benchmark environments with formally provable theoretical advantages over classical counterparts.However,despite the progress of quantum processors and the emergence of quantum computing clouds,implementing quantum reinforcement learning algorithms utilizing parameterized quantum circuits(PQCs)on NISQ devices remains infrequent.In this work,we take the first step towards executing benchmark quantum reinforcement problems on real devices equipped with at most 136 qubits on the BAQIS Quafu quantum computing cloud.The experimental results demonstrate that the policy agents can successfully accomplish objectives under modified conditions in both the training and inference phases.Moreover,we design hardware-efficient PQC architectures in the quantum model using a multi-objective evolutionary algorithm and develop a learning algorithm that is adaptable to quantum devices.We hope that the Quafu-RL can be a guiding example to show how to realize machine learning tasks by taking advantage of quantum computers on the quantum cloud platform.

Quafu-Qcover:Explore combinatorial optimization problems on cloud-based quantum computers

We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm(QAOA).It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization(QUBO)model and its corresponding Ising model,which can be subsequently transformed into a weight graph.The core of Qcover relies on a graph decomposition-based classical algorithm,which efficiently derives the optimal parameters for the shallow QAOA circuit.Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers.Compared to a general-purpose compiler,our compiler demonstrates the ability to generate shorter circuit depths,while also exhibiting superior speed performance.Additionally,the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time,utilizing the most recent calibration data from the superconducting quantum devices.This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity.The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time,enabling asynchronous processing.Moreover,it incorporates modules for results preprocessing and visualization,facilitating an intuitive display of solutions for combinatorial optimization problems.We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.

N-doped graphene quantum dot-decorated N-TiO2/P-doped porous hollow g-C_(3)N_(4) nanotube composite photocatalysts for antibiotic photodegradation and H2 production

Exclusive responsiveness to ultraviolet light (~3.2 eV) and high photogenerated charge recombination rate are the two primary drawbacks of pure TiO_(2). We combined N-doped graphene quantum dots (N-GQDs), morphology regulation, and heterojunction construction strategies to synthesize N-GQD/N-doped TiO_(2)/P-doped porous hollow g-C_(3)N_(4) nanotube (PCN) composite photocatalysts (denoted as G-TPCN). The optimal sample (G-TPCN doped with 0.1wt% N-GQD, denoted as 0.1% G-TPCN) exhibits significantly enhanced photoabsorption, which is attributed to the change in bandgap caused by elemental doping (P and N), the improved light-harvesting resulting from the tube structure, and the upconversion effect of N-GQDs. In addition, the internal charge separation and transfer capability of0.1% G-TPCN are dramatically boosted, and its carrier concentration is 3.7, 2.3, and 1.9 times that of N-TiO_(2), PCN, and N-TiO_(2)/PCN(TPCN-1), respectively. This phenomenon is attributed to the formation of Z-scheme heterojunction between N-TiO_(2) and PCNs, the excellent electron conduction ability of N-GQDs, and the short transfer distance caused by the porous nanotube structure. Compared with those of N-TiO_(2), PCNs, and TPCN-1, the H2 production activity of 0.1%G-TPCN under visible light is enhanced by 12.4, 2.3, and 1.4times, respectively, and its ciprofloxacin (CIP) degradation rate is increased by 7.9, 5.7, and 2.9 times, respectively. The optimized performance benefits from excellent photoresponsiveness and improved carrier separation and migration efficiencies. Finally, the photocatalytic mechanism of 0.1% G-TPCN and five possible degradation pathways of CIP are proposed. This study clarifies the mechanism of multiple modification strategies to synergistically improve the photocatalytic performance of 0.1% G-TPCN and provides a potential strategy for rationally designing novel photocatalysts for environmental remediation and solar energy conversion.

Unbound^(28)O,the heaviest oxygen isotope observed:a cutting-edge probe for testing nuclear models

The beyond-dripline oxygen isotopes^(27,28)O were recently observed at RIKEN,and were found to be unbound decaying into^(24)O by emitting neutrons.The unbound feature of the heaviest oxygen isotope,^(28)O,provides an excellent test for stateof-the-art nuclear models.The atomic nucleus is a self-organized quantum manybody system comprising specific numbers of protons Z and neutrons N.

Coupling of BiOCl Ultrathin Nanosheets with Carbon Quantum Dots for Enhanced Photocatalytic Performance

Over the past few decades,photocatalysis technology has received extensive attention because of its potential to mitigate or solve energy and environmental pollution problems.Designing novel materials with outstanding photocatalytic activities has become a research hotspot in this field.In this study,we prepared a series of photocatalysts in which BiOCl nanosheets were modified with carbon quantum dots(CQDs)to form CQDs/BiOCl composites by using a simple solvothermal method.The photocatalytic performance of the resulting CQDs/BiOCl composite photocatalysts was assessed by rhodamine B and tetracycline degradation under visible-light irradiation.Compared with bare BiOCl,the photocatalytic activity of the CQDs/BiOCl composites was significantly enhanced,and the 5 wt%CQDs/BiOCl composite exhibited the highest photocatalytic activity with a degradation efficiency of 94.5%after 30 min of irradiation.Moreover,photocatalytic N_(2)reduction performance was significantly improved after introducing CQDs.The 5 wt%CQDs/BiOCl composite displayed the highest photocatalytic N_(2)reduction performance to yield NH_3(346.25μmol/(g h)),which is significantly higher than those of 3 wt%CQDs/BiOCl(256.04μmol/(g h)),7 wt%CQDs/BiOCl(254.07μmol/(g h)),and bare BiOCl(240.19μmol/(g h)).Our systematic characterizations revealed that the key role of CQDs in improving photocatalytic performance is due to their increased light harvesting capacity,remarkable electron transfer ability,and higher photocatalytic activity sites.

Physical Layer Encryption of OFDM-PON Based on Quantum Noise Stream Cipher with Polar Code

Orthogonal frequency division multiplexing passive optical network(OFDM-PON) has superior anti-dispersion property to operate in the C-band of fiber for increased optical power budget. However,the downlink broadcast exposes the physical layer vulnerable to the threat of illegal eavesdropping. Quantum noise stream cipher(QNSC) is a classic physical layer encryption method and well compatible with the OFDM-PON. Meanwhile, it is indispensable to exploit forward error correction(FEC) to control errors in data transmission. However, when QNSC and FEC are jointly coded, the redundant information becomes heavier and thus the code rate of the transmitted signal will be largely reduced. In this work, we propose a physical layer encryption scheme based on polar-code-assisted QNSC. In order to improve the code rate and security of the transmitted signal, we exploit chaotic sequences to yield the redundant bits and utilize the redundant information of the polar code to generate the higher-order encrypted signal in the QNSC scheme with the operation of the interleaver.We experimentally demonstrate the encrypted 16/64-QAM, 16/256-QAM, 16/1024-QAM, 16/4096-QAM QNSC signals transmitted over 30-km standard single mode fiber. For the transmitted 16/4096-QAM QNSC signal, compared with the conventional QNSC method, the proposed method increases the code rate from 0.1 to 0.32 with enhanced security.

Proton‑Prompted Ligand Exchange to Achieve High‑Efficiency CsPbI_(3) Quantum Dot Light‑Emitting Diodes

CsPbI_(3)perovskite quantum dots(QDs)are ideal materials for the next generation of red light-emitting diodes.However,the low phase stability of CsPbI_(3)QDs and long-chain insulating capping ligands hinder the improvement of device performance.Traditional in-situ ligand replacement and ligand exchange after synthesis were often difficult to control.Here,we proposed a new ligand exchange strategy using a proton-prompted insitu exchange of short 5-aminopentanoic acid ligands with long-chain oleic acid and oleylamine ligands to obtain stable small-size CsPbI_(3)QDs.This exchange strategy maintained the size and morphology of CsPbI_(3)QDs and improved the optical properties and the conductivity of CsPbI_(3)QDs films.As a result,high-efficiency red QD-based light-emitting diodes with an emission wavelength of 645 nm demonstrated a record maximum external quantum efficiency of 24.45%and an operational half-life of 10.79 h.

Design of a novel hybrid quantum deep neural network in INEQR images classification

We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantum circuit, thereby propose a novel hybrid quantum deep neural network(HQDNN) used for image classification. After bilinear interpolation reduces the original image to a suitable size, an improved novel enhanced quantum representation(INEQR) is used to encode it into quantum states as the input of the HQDNN. Multi-layer parameterized quantum circuits are used as the main structure to implement feature extraction and classification. The output results of parameterized quantum circuits are converted into classical data through quantum measurements and then optimized on a classical computer. To verify the performance of the HQDNN, we conduct binary classification and three classification experiments on the MNIST(Modified National Institute of Standards and Technology) data set. In the first binary classification, the accuracy of 0 and 4 exceeds98%. Then we compare the performance of three classification with other algorithms, the results on two datasets show that the classification accuracy is higher than that of quantum deep neural network and general quantum convolutional neural network.

Detecting the quantum phase transition from the perspective of quantum information in the Aubry–André model

We investigate the effectiveness of entropic uncertainty, entanglement and steering in discerning quantum phase transitions(QPTs). Specifically, we observe significant fluctuations in entropic uncertainty as the driving parameter traverses the phase transition point. It is observed that the entropic uncertainty, entanglement and quantum steering, based on the electron distribution probability, can serve as indicators for detecting QPTs. Notably, we reveal an intriguing anticorrelation relationship between entropic uncertainty and entanglement in the Aubry–André model. Moreover, we explore the feasibility of detecting a QPT when the period parameter is a rational number. These observations open up new and efficient avenues for probing QPTs.

Holevo bound independent of weight matrices for estimating two parameters of a qubit

Holevo bound plays an important role in quantum metrology as it sets the ultimate limit for multi-parameter estimations,which can be asymptotically achieved.Except for some trivial cases,the Holevo bound is implicitly defined and formulated with the help of weight matrices.Here we report the first instance of an intrinsic Holevo bound,namely,without any reference to weight matrices,in a nontrivial case.Specifically,we prove that the Holevo bound for estimating two parameters of a qubit is equivalent to the joint constraint imposed by two quantum Cramér–Rao bounds corresponding to symmetric and right logarithmic derivatives.This weightless form of Holevo bound enables us to determine the precise range of independent entries of the mean-square error matrix,i.e.,two variances and one covariance that quantify the precisions of the estimation,as illustrated by different estimation models.Our result sheds some new light on the relations between the Holevo bound and quantum Cramer–Rao bounds.Possible generalizations are discussed.

Quantum circuit-based proxy blind signatures:A novel approach and experimental evaluation on the IBM quantum cloud platform

This paper presents a novel approach to proxy blind signatures in the realm of quantum circuits,aiming to enhance security while safeguarding sensitive information.The main objective of this research is to introduce a quantum proxy blind signature(QPBS)protocol that utilizes quantum logical gates and quantum measurement techniques.The QPBS protocol is constructed by the initial phase,proximal blinding message phase,remote authorization and signature phase,remote validation,and de-blinding phase.This innovative design ensures a secure mechanism for signing documents without revealing the content to the proxy signer,providing practical security authentication in a quantum environment under the assumption that the CNOT gates are securely implemented.Unlike existing approaches,our proposed QPBS protocol eliminates the need for quantum entanglement preparation,thus simplifying the implementation process.To assess the effectiveness and robustness of the QPBS protocol,we conduct comprehensive simulation studies in both ideal and noisy quantum environments on the IBM quantum cloud platform.The results demonstrate the superior performance of the QPBS algorithm,highlighting its resilience against repudiation and forgeability,which are key security concerns in the realm of proxy blind signatures.Furthermore,we have established authentic security thresholds(82.102%)in the presence of real noise,thereby emphasizing the practicality of our proposed solution.