Electrode Interfaces Switchable by Physical and Chemical Signals Operating as a Platform for Information Processing

The echo information processing platform is an important part of the phased array radar system. With the increasing demands of the airborne phased array radar mission on bus transmission bandwidth, computational processing speed, system response time, and data processing capability, the traditional echo information processing platform has been difficult to meet the requirements of technological development. Based on the advantages of high transmission bandwidth, rich I/O resources and strong scalability of VPX bus, this paper proposes a design scheme of echo information processing platform based on VPX bus, focusing on the composition of information processing platform and the design principle of each functional module. Based on the idea of dataflow driving, a new peer-to-peer backplane architecture is adopted. The test results show that the information processing platform only needs 20.2s to complete 32K*32K complex image processing. The performance is superior, stable and reliable.

We propose a scheme of an optomechanical system that optimizes entanglement in nanomechanical resonators through quantum state transfer of intracavity squeezing and squeezed reservoir field sources assisted by radiation pressure. The system is driven by red-detuned laser fields, which enable simultaneous cooling of the mechanical resonators and facilitate the quantum state transfer in a weak coupling and good cavity limit. Specifically, the mechanical entanglement is quantified using logarithmic negativity within the bipartite Gaussian states of the two mechanical modes. The results show that several key parameters, including the parametric phase and nonlinear gain of the non-degenerate optical parametric amplifier, the strength of the squeezing reservoir, optomechanical cooperativity, thermal excitation of phonons, and the temperature of mechanical baths, strongly influence the degree of mechanical entanglement. Hence, the findings indicate that careful tuning of the parameters can enable control over the enhancement of entanglement robustness, suggesting that this optomechanical scheme provides a viable pathway for applications in quantum sensing and information processing • An optomechanical scheme enhances entanglement via squeezing and red-detuned driving. • Entanglement is quantified using logarithmic negativity from the covariance matrix. • Key parameters: squeezing strength, phase, gain, cooperativity, and bath temperature. • Coupling to a two-mode squeezed vacuum boosts robustness to mechanical thermal noise. • The scheme offers a viable platform for quantum metrology and information processing.

This study investigates the quantum dynamics of three-level Stark-shifted atomic systems under the influence of a Nonlinear Kerr Medium (NLKM), focusing on the interplay between Quantum Fisher Information (QFI), Von Neumann Entropy (VNE), and photon-mediated interactions. By analyzing the temporal evolution of QFI (quantifying parameter estimation precision) and VNE (measuring quantum entanglement (QE), we demonstrate how Kerr nonlinearity (chi), Stark shifts (beta), phase (phi), and photon numbers govern system behavior. Key findings reveal that lower chi values (e.g., chi =0.3) induce oscillatory QFI decay and rapid VNE growth, driven by atomic motion and NLKM interactions, with QFI peaks inversely correlated to VNE dips. Higher chi (text{1,3}) stabilizes both metrics, suppressing decoherence and entanglement fluctuations. Elevated photon numbers enhance stability by strengthening field-atom correlations, reducing oscillation amplitudes (particularly at low chi), and mitigating quantum fluctuations. The Stark effect (SE) amplifies energy-level shifts, while phase adjustments introduce asymmetries in quantum interference. These results highlight the system’s tunability via chi , beta . phi, and photon density. They position it as a versatile platform for quantum metrology and information processing, where precision, entanglement stability, and photon-mediated coherence are critical. Kerr interactions suppress long-time coherence and entanglement, while when chi =0, Stark shifts can induce mild, transient quantum correlations. These dynamics are essential for controlling entanglement in cavity QED systems, especially when precise metrological performance is desired.

To functionally emulate the history-dependent plasticity and electromagnetic induction effects inherent in biochemical synapses, this paper proposes a heterogeneous neural network model in which Hindmarsh–Rose (HR) neurons and FitzHugh–Nagumo (FHN) neurons are coupled via a synaptic connection composed of a meminductor in series with a resistor. This architecture explicitly decouples synaptic function: the linear resistor models the instantaneous conductive pathway, while the meminductor implements the history-dependent plastic pathway. The complex firing dynamics of the coupled system are systematically investigated through bifurcation diagrams, Lyapunov exponent spectra, phase portraits, and time-series analysis. Results show that variations in synaptic coupling strength and coupling resistance can induce transitions among diverse firing patterns, including chaotic spiking, periodic bursting, and periodic–chaotic alternations. Crucially, the meminductive synapse introduces activity-dependent multistability, manifested as the coexistence of multiple firing patterns determined by its initial internal state. Phase synchronization analysis further demonstrates that adjusting the coupling resistance provides an independent control mechanism to effectively enhance or suppress synchronous firing between the two heterogeneous neurons, even under fixed coupling strength. Finally, the physical feasibility of the system is validated through successful digital implementation on a Digital Signal Processor (DSP) platform, with experimental measurements showing excellent agreement with numerical simulations. This study establishes the meminductor as a biomimetically grounded element for chemical synapse emulation and provides a dynamically rich, hardware-validated platform for neuromorphic computing and information processing.

The paper expects to improve the efficiency and intelligence of somatosensory recognition technology in the application of physical education teaching practice. Firstly, the combination of induction recognition technology and the Internet is used. Secondly, through the Kinect sensor, bone data are acquired. Finally, the hidden Markov model (HMM) is used to simulate the experimental data. On the simulation results, a gait recognition algorithm is proposed. The gait recognition algorithm is used to identify the motion behaviour, and the results are displayed in the Web (World Wide Web) end built by the cloud server. Meantime, in view of the existing problems in the practice of physical education, combined with the establishment and operation of the Digital Twins (DTs) system, the camera source recognition architecture is carried out since the twin network and the two network branches share weights. This paper analyses these problems since the application of somatosensory recognition technology and puts forward the improvement methods. For the single problem of equipment in physical education, this paper puts forward the monitoring and identification function of the cloud server. It is to transmit data through Hypertext Transfer Protocol (HTTP) and locate and collect data through a monitoring terminal. For the lack of comprehensiveness and balance of sports plans, this paper proposes a scientific training plan and process customization based on Body Mass Index (BMI), analyses real‐time data in the cloud, and makes scientific customization plans according to different students’ physical conditions. Moreover, 25 participants are invited to carry out the exercise detection and analysis experiment, and the joint monitoring of their daily movements is tested. This process has completed the design of a feasible and accurate platform for information collection and processing, which is convenient for managers and educators to comprehensively and scientifically master and manage the physical level and training of college students. The proposed method improves the recognition rate of the camera source to some extent and has important exploration significance in the field of action recognition.

Welcome to IPSN 2012, the Eleventh ACM/IEEE Conference on Information Processing in Sensing Networks! This year marks the first time IPSN is held in Asia, recognizing the region's growing interest and activities in the areas of sensor networks, Internet-of-Things (IoT), and Cyber-Physical Systems (CPS). We hope that you will enjoy this diverse conference that is a leading venue for publications and idea exchange on sensor networks. IPSN is unique in its broad coverage of the field, ranging from foundations to system implementation and platforms. It is a meeting point of theory and practice, as embodied in its two tracks: Information Processing (IP) and Sensor Platforms, Tools and Design Methods (SPOTS). In an effort to further unify the conference this year, we formed a joint technical program committee (TPC) and held a single TPC meeting. Authors could select the IP or the SPOTS track for their submissions and TPC members were able to provide their review preferences across all papers submitted to the conference. We believe that in this way, each paper received the most relevant and useful set of reviews. The field of sensor networks has shown a continuing strength over the years as indicated by the number and the quality of submissions this year: 53 in the SPOTS track and 94 in the IP track, for a total of 147 submissions. These submissions underwent a two-stage review process during which each paper received at least three reviews and occasionally up to seven reviews. An online discussion followed the review process during which the set of papers that were discussed in the TPC meeting were selected. The set of accepted papers were decided during a face-to-face TPC meeting. 22 papers were selected for publication out of which 12 were in the IP track and 10 in the SPOTS track. As in the past, the exciting demo and poster session provides an opportunity for attendees to examine and discuss the latest in sensing devices, systems and applications, following a special session with a rapid-fire series of short "pitch" talks from the authors of posters and demos. A new addition to the program this year is the PhD Forum where students working in the field present their dissertation ideas and get critical feedback from a panel of experts. The main conference is complemented by a number of workshops and tutorials in emerging or adjacent areas of sensor networks such as mobile, IoT, and smart objects.

A large qubit capacity and an individual readout capability are two crucial requirements for large-scale quantum computing and simulation1. As one of the leading physical platforms for quantum information processing, the ion trap has achieved a quantum simulation of tens of ions with site-resolved readout in a one-dimensional Paul trap2-4 and of hundreds of ions with global observables in a two-dimensional (2D) Penning trap5,6. However, integrating these two features into a single system is still very challenging. Here we report the stable trapping of 512 ions in a 2D Wigner crystal and the sideband cooling of their transverse motion. We demonstrate the quantum simulation of long-range quantum Ising models with tunable coupling strengths and patterns, with or without frustration, using 300 ions. Enabled by the site resolution in the single-shot measurement, we observe rich spatial correlation patterns in the quasi-adiabatically prepared ground states, which allows us to verify quantum simulation results by comparingthe measured two-spin correlations with the calculated collective phonon modes and with classical simulated annealing. We further probe the quench dynamics of the Ising model in a transverse field to demonstrate quantum sampling tasks. Our work paves the way for simulating classically intractable quantum dynamics and for running noisy intermediate-scale quantum algorithms7,8 using 2D ion trap quantum simulators.

Diamond is a promising platform for quantum information processing as it can host highly coherent qubits that could allow for the construction of large quantum registers. A prerequisite for such devices is a coherent interaction between nitrogen-vacancy (NV) electron spins enabling scalable entanglement. Entanglement between dipolar-coupled NV spin pairs has been demonstrated but with a limited fidelity, and its error sources have not been characterized. Here, we design and implement a robust two-qubit gate between NV electron spins in diamond and quantify the influence of multiple error sources on the gate performance. Experimentally, we demonstrate a record gate fidelity of F2q=(96.0±2.5)% under ambient conditions. Our identification of the dominant errors paves the way towards NV-NV gates beyond the error correction threshold.

Graph states are one of the most significant classes of entangled states, serving as the quantum resources for quantum technologies. Recently, integrated quantum photonics is becoming a promising platform for quantum information processing, enabling the generation, manipulation, and measurement of photonic quantum states. This article summarizes state-of-the-art experimental progress and advances in the chip-based photonic graph states.

We cast diffraction-based interferometry in the framework of post-selected unitary description towards enabling it as a platform for quantum information processing (QIP). We express slit-diffraction as an infinite-dimensional transformation and truncate it to a finite-dimensional transfer matrix by post-selecting modes. Using such a framework with classical fields we show that a customized double-slit setup is effectively a lossy beam splitter in a post-selected sense. Diffraction optics provides a robust alternative to conventional multi-beam interferometry with scope for miniaturization, and also has applications in matter wave interferometry. In this work, the classical treatment of slit-diffraction sets the stage for quantization of fields and implementing higher-dimensional QIP like that done with other platforms such as orbital angular momentum.

Optically addressable solid-state color center spin qubits have become important platforms for quantum information processing, quantum networks and quantum sensing. The readout of color center spin states with optically detected magnetic resonance (ODMR) technology is traditionally based on Stokes excitation, where the energy of the exciting laser is higher than that of the emission photons. Here, we investigate an unconventional approach using anti-Stokes excitation to detect the ODMR signal of silicon vacancy defect spin in silicon carbide, where the exciting laser has lower energy than the emitted photons. Laser power, microwave power and temperature dependence of the anti-Stokes excited ODMR are systematically studied, in which the behavior of ODMR contrast and linewidth is shown to be similar to that of Stokes excitation. However, the ODMR contrast is several times that of the Stokes excitation. Coherent control of silicon vacancy spin under anti-Stokes excitation is then realized at room temperature. The spin coherence properties are the same as those of Stokes excitation, but with a signal contrast that is around three times greater. To illustrate the enhanced spin readout contrast under anti-Stokes excitation, we also provide a theoretical model. The experiments demonstrate that the current anti-Stokes excitation ODMR approach has promising applications in quantum information processing and quantum sensing.

Rare earth ions in crystals exhibit narrow spectral features and hyperfine-split ground states with exceptionally long coherence times. These features make them ideal platforms for quantum information processing in the solid state. Recently, we reported on the first high-resolution spectroscopy of single ions in yttrium orthosilicate nanocrystals via the transition at a wavelength of 488 nm. Here we show that individual praseodymium ions can also be detected on the more commonly studied transition at 606 nm. In addition, we present the first measurements of the second-order autocorrelation function, fluorescence lifetime, and emission spectra of single ions in this system as well as their polarization dependencies on both transitions. Furthermore, we demonstrate that by a proper choice of the crystallite, one can obtain narrower spectral lines and, thus, resolve the hyperfine levels of the excited state. We expect our results to make single-ion spectroscopy accessible to a larger scientific community.

Arrays of identical and individually addressable qubits lay the foundation for the creation of scalable quantum hardware such as quantum processors and repeaters. Silicon-vacancy (SiV) centers in diamond offer excellent physical properties such as low inhomogeneous broadening, fast photon emission, and a large Debye–Waller factor. The possibility for all-optical ultrafast manipulation and techniques to extend the spin coherence times makes them promising candidates for qubits. Here, we have developed arrays of nanopillars containing single (SiV) centers with high yield, and we demonstrate ultrafast all-optical complete coherent control of the excited state population of a single SiV center at the optical transition frequency. The high quality of the chemical vapor deposition (CVD) grown SiV centers provides excellent spectral stability, which allows us to coherently manipulate and quasi-resonantly read out the excited state population of individual SiV centers on picosecond timescales using ultrafast optical pulses. Furthermore, this work opens new opportunities to create a scalable on-chip diamond platform for quantum information processing and scalable nanophotonics applications.

Hybrid quantum circuits combining advantages of each individual system have provided a promising platform for quantum information processing. Here we propose an experimental scheme to directly couple a transmon qubit to an individual spin in the nitrogen-vacancy (NV) center, with a coupling strength three orders of magnitude larger than that for a single spin coupled to a microwave cavity. This direct coupling between the transmon and the NV center could be utilized to make a transmon bus, leading to a coherently virtual exchange among different single spins. Furthermore, we demonstrate that, by coupling a transmon to a low-density NV ensemble, a SWAP operation between the transmon and NV ensemble is feasible and a quantum non-demolition measurement on the state of NV ensemble can be realized on the cavity-transmon-NV-ensemble hybrid system. Moreover, on this system, a virtual coupling can be achieved between the cavity and NV ensemble, which is much larger in magnitude than the direct coupling between the cavity and the NV ensemble. The photon state in cavity can be thus stored into NV spins more efficiently through this virtual coupling.

Living systems use enzymatic reaction networks to process biochemical information and make decisions in response to external or internal stimuli. Herein, we present a modular and reusable platform for molecular information processing using enzymes immobilised in hydrogel beads and compartmentalised in a continuous stirred tank reactor. We demonstrate how this setup allows us to perform simple arithmetic operations, such as addition, subtraction and multiplication, using various concentrations of substrates or inhibitors as inputs and the production of a fluorescent molecule as the readout.