The gravitational wave (GW) observations indicate the beginning of a new era, probing the Universe including the test of Einstein’s theory of general relativity (GR) and understanding of the black holes formation and structure. Taiji is a space-based GW detection mission proposed by China that is planned to be launched soon. In order to lay a common ground for Taiji related data analysis challenges, Taiji Data Challenge (TDC) is proposed in one paper of current issue. Building a data challenge is critical for scientists to develop data analysis algorithms and pipelines for future space-based GW observations. A community of researchers who can collaboratively contribute to the development of Taiji's data analysis pipelines and join the journey of exploring the universe and making new discoveries with Taiji Collaboration are needed. For more details, please see the article “Taiji data challenge for exploring gravitational wave universe” by Zhixiang Ren, et al., Front. Phys. 18(6), 64302 (2023). [Photo credits: Haihong Jia & Min Zhang at Taiji Laboratory for Gravitational Wave Universe and International Centre for Theoretical Physics Asia-Pacific (ICTP-AP), University of Chinese Academy of Science (UCAS), Beijing 100049, China]
2023,18 (5)
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In recent years, there has been widespread attention and discourse surrounding the field of distributed quantum computation. In comparison to centralized quantum computation, distributed quantum computation requires fewer qubits per node and shallower quantum circuits, making it more efficient in performing quantum computing tasks. We propose a distributed exact Grover algorithm (DEGA) that can solve the exact search problem for single target string. Specifically, (i) our algorithm is exact, which means the theoretical probability of finding the objective state is 100%; (ii) the depth of our circuit is less than the circuit depths of the original and modified Grover's algorithms. It only depends on the parity of n, and it is not deepened as n increases; (iii) we provide particular situations of our DEGA on MindQuantum (a quantum software) to demonstrate the practicality and validity of our method. Since our circuit is shallower, it will be more resistant to the depolarization channel noise. For more details, please refer to the article entitled “Distributed exact Grover’s algorithm” by Xu Zhou, Daowen Qiu, and Le Luo, Front. Phys. 18(5), 51305 (2023). [Photo credits: Xu Zhou at QUDOOR Co, Ltd.]
2023,18 (4)
Given the structure of a large-scale complex network and the nodal dynamics are known, can we predict all the possible synchronization patterns to be emerged and, in addition, the conditions for generating these patterns? Whereas this question has been broadly interested and extensively studied, the existing methods require a priori knowledge of the network symmetries and, additionally, a perfect network symmetry. Recently, Huawei Fan, et al., proposed a general framework for exploring cluster synchronization behaviors in general large-size complex networks. The key of the new framework lies in the exploitation of the eigenvectors of the network coupling matrix, which has been largely overlooked in previous studies but in fact plays crucial roles in inferring the network dynamics. With the new framework, the authors are able to predict theoretically not only all the synchronization patterns to be emerged on the network, but also the critical couplings for generating the patterns and the sequence of the patterns in the transition to global synchronization. For more details, please refer to the article entitled “Eigenvector-based analysis of cluster synchronization in general complex network of coupled chaotic oscillators” by Huawei Fan, Ya Wang, and Xingang Wang, Front. Phys. 18(4), 45302 (2023).
2023,18 (3)
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Circuits provide ideal platforms of topological phases and matter, yet the study of topological circuits in the strongly nonlinear regime, has been lacking. We propose and experimentally demonstrate strongly nonlinear topological phases and transitions in one-dimensional electrical circuits composed of nonlinear capacitors. Nonlinear topological interface modes arise on domain walls of the circuit lattices, whose topological phases are controlled by the amplitudes of nonlinear voltage waves. Experimentally measured topological transition amplitudes are in good agreement with those derived from nonlinear topological band theory. Our prototype paves the way towards flexible metamaterials with amplitude-controlled rich topological phases and is readily extendable to two and three-dimensional systems that allow novel applications. For more details, please refer to the article entitled “Strongly nonlinear topological phases of cascaded topoelectrical circuits” by Jijie Tang, et al., Front. Phys. 18(3), 33311 (2023). [Photo credit: Feng Li at Beijing Institute of Technology.]
2023,18 (2)
Shenzhen Institute for Quantum Science and Engineering (SIQSE), founded in January 2018, celebrated its fifth anniversary on January 19, 2023. Over the past five years, with the support of Shenzhen and Southern University of Science and Technology, SIQSE has powered the development of quantum technologies, grown into an impactful quantum center with the scale and expertise, and attracted talent researchers in quantum science and engineering worldwide. The scope of SIQSE covers all aspects of quantum technologies, including quantum computing, simulation, materials, and metrology. In honor of the institute's fifth anniversary, we published this special topic on “Embracing the Quantum Era: Celebrating the 5th Anniversary of Shenzhen Institute for Quantum Science and Engineering" (Eds.: Dapeng Yu, Dawei Lu & Zhimin Liao).
2023,18 (1)
Oxygen electrocatalysts are of great importance for the air electrode in zinc–air batteries (ZABs). Owing to large surface area, high electrical conductivity and ease of modification, two-dimensional (2D) materials have been widely studied as oxygen electrocatalysts for the rechargable ZABs. The elaborately modified 2D materials-based electrocatalysts, usually exhibit excellent performance toward the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), which have attracted extensive interests of worldwide researchers. Given the rapid development of bifunctional electrocatalysts toward ORR and OER, the latest progress of non-noble electrocatalysts based on layered double hydroxides (LDHs), graphene, and MXenes are intensively reviewed. The discussion ranges from fundamental structure, synthesis, electrocatalytic performance of these catalysts, as well as their applications in the rechargeable ZABs. Finally, the challenges and outlook are provided for further advancing the commercialization of rechargeable ZABs. For more details, please refer to the article entitled “Bifunctional oxygen electrocatalysts for rechargeable zinc−air battery based on MXene and beyond” by Jing Zhang, et al., Front. Phys. 18(1), 13603 (2023). [Photo credit: Ruguang Ma at Suzhou University of Science and Technology.]
2022,17 (6)
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Two-dimensional (2D) semiconductors are emerging as promising candidates for the next-generation nanoelectronics. As a type of unique channel materials, 2D semiconducting transition metal dichalcogenides (TMDCs), such as MoS2 and WS2, exhibit great potential for the state-of-the-art field-effect transistors owing to their atomically thin thicknesses, dangling-band free surfaces, and abundant band structures. Even so, the device performances of 2D semiconducting TMDCs are still failing to reach the theoretical values so far, which is attributed to the intrinsic defects, excessive doping, and daunting contacts between electrodes and channels. In this article, the authors reviewed the up-to-date three strategies for improving the device performances of 2D semiconducting TMDCs: (i) the controllable synthesis of wafer-scale 2D semiconducting TMDCs single crystals to reduce the evolution of grain boundaries, (ii) the ingenious doping of 2D semiconducting TMDCs to modulate the band structures and suppress the impurity scatterings, and (iii) the optimization design of interfacial contacts between electrodes and channels to reduce the Schottky barrier heights and contact resistances. For more details, please refer to the article entitled “Improving the device performances of two-dimensional semiconducting transition metal dichalcogenides: Three strategies” by Mo Cheng, et al., Front. Phys. 17(6), 63601 (2022). [Photo credit: Jianping Shi at Wuhan University.]
2022,17 (5)
The field-free spin-orbit torque (SOT) switching of perpendicular magnetization is a prerequisite for realizing fast, high-density, and low-power magnetic memories and logic devices. To date, field-free SOT switching of perpendicular magnetization has been realized through various asymmetric designs in the film structures, such as by adding additional functional layers or grow wedge shaped structures. Here we demonstrate a new strategy to realize field-free switching of perpendicular magnetization by exploring the asymmetry in the substrates. By growing the L10-FePt film on vicinal substrates, we realize the field-free switching of L10-FePt. This approach does not need to create asymmetry in the film structure, thus greatly simplifies the SOT film structure and is easier for mass production. For more details, please refer to the article entitled “Field-free switching through bulk spin-orbit torque in L10-FePt films deposited on vicinal substrates” by Yongming Luo, et al., Front. Phys. 17(5), 53511 (2022). [Photo credit: Yongming Luo & Tiejun Zhou at Hangzhou Dianzi University.]
The field-free spin-orbit torque (SOT) switching of perpendicular magnetization is a prerequisite for realizing fast, high-density, and low-power magnetic memories and logic devices. To date, field-free SOT switching of perpendicular magnetization has been realized through various asymmetric designs in the film structures, such as by adding additional functional layers or grow wedge shaped structures. Here we demonstrate a new strategy to realize field-free switching of perpendicular magnetization by exploring the asymmetry in the substrates. By growing the L10-FePt film on vicinal substrates, we realize the field-free switching of L10-FePt. This approach does not need to create asymmetry in the film structure, thus greatly simplifies the SOT film structure and is easier for mass production. For more details, please refer to the article entitled “Field-free switching through bulk spin-orbit torque in L10-FePt films deposited on vicinal substrates” by Yongming Luo, et al., Front. Phys. 17(5), 53511 (2022). [Photo credit: Yongming Luo & Tiejun Zhou at Hangzhou Dianzi University.]
2022,17 (4)
Transition metal dichalcogenides (TMDCs) have attracted extensive attention due to their favorable electronic, mechanical, optical properties and the interesting semiconducting electrical properties. However, the requirements of optoelectric devices for suitable band gap, ultrahigh responsivity and carrier mobility pose new challenges for TMDCs optoelectric devices. The emergence of TMDCs heterostructures perfectly solved this problem. The complementary properties of different heterostructure materials make them attractive materials for optoelectric devices. Here we review the research on TMDCs heterostructure-based optoelectric devices from both DFT theoretical calculations and experimental studies. The prepared nano-optoelectric devices such as p–n diode, photodetectors, ultrahigh photoresponsive device show great application value. For more details, please refer to the article entitled “Transition metal dichalcogenides (TMDCs) heterostructures: Optoelectric properties” by Rui Yang, et al., Front. Phys. 17(4), 43202 (2022). [Photo credit: Rui Yang & Mengtao Sun at University of Science and Technology Beijing.]
Transition metal dichalcogenides (TMDCs) have attracted extensive attention due to their favorable electronic, mechanical, optical properties and the interesting semiconducting electrical properties. However, the requirements of optoelectric devices for suitable band gap, ultrahigh responsivity and carrier mobility pose new challenges for TMDCs optoelectric devices. The emergence of TMDCs heterostructures perfectly solved this problem. The complementary properties of different heterostructure materials make them attractive materials for optoelectric devices. Here we review the research on TMDCs heterostructure-based optoelectric devices from both DFT theoretical calculations and experimental studies. The prepared nano-optoelectric devices such as p–n diode, photodetectors, ultrahigh photoresponsive device show great application value. For more details, please refer to the article entitled “Transition metal dichalcogenides (TMDCs) heterostructures: Optoelectric properties” by Rui Yang, et al., Front. Phys. 17(4), 43202 (2022). [Photo credit: Rui Yang & Mengtao Sun at University of Science and Technology Beijing.]
2022,17 (3)
In the noise-intermediate-scale quantum (NISQ) era, a scalable error-corrected quantum computer is still unviable but a large degree of controllability has been available in a broad spectrum of NISQ devices. Thus, under what conditions our quantum physical systems will have the optimal computational power within the limited computing resource, which is a crucial problem. Here we handle this problem in the framework of quantum reservoir computing. Our quantum reservoir is a long-range disorder spin chain and there is a phase transition from the quantum many-body localized (MBL) phase to the ergodic phase. Our research paper finds optimal learning performance near the MBL-to-ergodic transition. This leads to a guiding principle of quantum reservoir engineering at the edge of quantum ergodicity reaching optimal learning power for generic complex reservoir learning tasks. For more details, please refer to the article entitled “The reservoir learning power across quantum many-body localization transition” by Wei Xia, et al., Front. Phys. 17(3), 33506 (2022). [Photo credit: Wei Xia & Xiaopeng Li at Fudan University.]
In the noise-intermediate-scale quantum (NISQ) era, a scalable error-corrected quantum computer is still unviable but a large degree of controllability has been available in a broad spectrum of NISQ devices. Thus, under what conditions our quantum physical systems will have the optimal computational power within the limited computing resource, which is a crucial problem. Here we handle this problem in the framework of quantum reservoir computing. Our quantum reservoir is a long-range disorder spin chain and there is a phase transition from the quantum many-body localized (MBL) phase to the ergodic phase. Our research paper finds optimal learning performance near the MBL-to-ergodic transition. This leads to a guiding principle of quantum reservoir engineering at the edge of quantum ergodicity reaching optimal learning power for generic complex reservoir learning tasks. For more details, please refer to the article entitled “The reservoir learning power across quantum many-body localization transition” by Wei Xia, et al., Front. Phys. 17(3), 33506 (2022). [Photo credit: Wei Xia & Xiaopeng Li at Fudan University.]
2022,17 (2)
he development of elaborate neural networks makes deep learning an accurate and efficient approach to solve some hard physical problems. This article proposes a novel hybrid network that integrates Long Short-Term Memory (LSTM) and residual network (ResNet), enabling the simulation of fast-oscillating quantum dynamics with a high-fidelity. Taking atomic condensate trapped in a double-well potential as an example, the efficiency of ResNet learning for the population dynamics is shown to be deeply improved as compared to the direct learning, owing to the verification of the dynamical periodicity in advance by the LSTM. Moreover, the LSTM makes credible predictions of higher-frequency oscillating behaviors in the macroscopic quantum self-trapping regime even if the numerical results are inaccessible due to the finite calculation precision. This hybrid neural network deserves a future study for simulating realistic dynamical evolutions in other complex physical systems. For more details, please refer to the article entitled “Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network” by Shurui Li, et al., Front. Phys. 17(2), 22504 (2022). [Photo credit: Jing Qian at East China Normal University.]
he development of elaborate neural networks makes deep learning an accurate and efficient approach to solve some hard physical problems. This article proposes a novel hybrid network that integrates Long Short-Term Memory (LSTM) and residual network (ResNet), enabling the simulation of fast-oscillating quantum dynamics with a high-fidelity. Taking atomic condensate trapped in a double-well potential as an example, the efficiency of ResNet learning for the population dynamics is shown to be deeply improved as compared to the direct learning, owing to the verification of the dynamical periodicity in advance by the LSTM. Moreover, the LSTM makes credible predictions of higher-frequency oscillating behaviors in the macroscopic quantum self-trapping regime even if the numerical results are inaccessible due to the finite calculation precision. This hybrid neural network deserves a future study for simulating realistic dynamical evolutions in other complex physical systems. For more details, please refer to the article entitled “Revisiting the dynamics of Bose-Einstein condensates in a double well by deep learning with a hybrid network” by Shurui Li, et al., Front. Phys. 17(2), 22504 (2022). [Photo credit: Jing Qian at East China Normal University.]
2022,17 (1)
Thermal expansion is a common phenomenon in nature. Most materials expand on heating and shrinks on cooling. Nevertheless, a few materials do behave oppositely, i.e., negative thermal expansion (NTE), like water below 4 centigrade. The phenomenon of NTE has attracted attention for its scientific curiosity and potential uses ranging from cooktops and dental fillings to mitigating the positive thermal expansion in composite materials. Increasing categories of NTE materials have been discovered in the last two and half decades. What causes these materials to shrink when heated? The review article entitled “Negative thermal expansion: Mechanisms and materials” by S. J. Zhang, et al. [Front. Phys. 16(5), 53302 (2021)] presents the most recent understanding on the origins of NTE phenomenon for each category of materials. These include anharmonic phonon vibration, magnetovolume effect, ferroelectrorestriction and charge transfer, etc. Besides, some problems affecting applications of NTE materials are discussed and strategies for discovering and design novel framework structured NET materials are also presented. [Photo credits: Erjun Liang, Zhengzhou University]
Thermal expansion is a common phenomenon in nature. Most materials expand on heating and shrinks on cooling. Nevertheless, a few materials do behave oppositely, i.e., negative thermal expansion (NTE), like water below 4 centigrade. The phenomenon of NTE has attracted attention for its scientific curiosity and potential uses ranging from cooktops and dental fillings to mitigating the positive thermal expansion in composite materials. Increasing categories of NTE materials have been discovered in the last two and half decades. What causes these materials to shrink when heated? The review article entitled “Negative thermal expansion: Mechanisms and materials” by S. J. Zhang, et al. [Front. Phys. 16(5), 53302 (2021)] presents the most recent understanding on the origins of NTE phenomenon for each category of materials. These include anharmonic phonon vibration, magnetovolume effect, ferroelectrorestriction and charge transfer, etc. Besides, some problems affecting applications of NTE materials are discussed and strategies for discovering and design novel framework structured NET materials are also presented. [Photo credits: Erjun Liang, Zhengzhou University]
