Experimental Implementation Research Articles

Digital quantum simulation of cosmological particle creation with IBM quantum computers

We use digital quantum computing to simulate the creation of particles in a dynamic spacetime. We consider a system consisting of a minimally coupled massive quantum scalar field in a spacetime undergoing homogeneous and isotropic expansion, transitioning from one stationary state to another through a brief inflationary period. We simulate two vibration modes, positive and negative for a given field momentum, by devising a quantum circuit that implements the time evolution. With this circuit, we study the number of particles created after the universe expands at a given rate, both by simulating the circuit and by actual experimental implementation on IBM quantum computers, consisting of hundreds of quantum gates. We find that state-of-the-art error mitigation techniques are useful to improve the estimation of the number of particles and the fidelity of the state.

Programmable photonic latch memory.

Significant advancements in integrated photonics have enabled high-speed and energy efficient systems for various applications, from data communications and high-performance computing to medical diagnosis, sensing, and ranging. However, data storage in these systems has been dominated by electronic memories that in addition to signal conversion between optical and electrical domains, necessitates conversion between analog to digital domains and electrical data movement between processor and memory that reduce the speed and energy efficiency. To date, scalable optical memory with optical control has remained an open problem. Here, we report an integrated photonic set-reset latch as a fundamental optical static memory unit based on universal optical logic gates. As a proof of concept, experimental implementation of the universal logic gates and realistic simulation of the latch are demonstrated on a programmable silicon photonic platform. Optical set, reset, and complementary outputs, scalability to a large number of memory units via the independent latch supply light, and compatibility with wavelength division multiplexing scheme and different photonic platforms enable more efficient and lower latency optical processing systems.

Experimental implementation of the peripheral nerve block clinical registry: an observational study

Background and aimsPeripheral nerve block (PNB) is commonly used, but there is a lack of data on its effectiveness and safety in the clinic. Therefore, anesthesiologists have limited insight into how they are faring in terms of both safety and efficacy. Additionally, No PNB registry is recorded in IRAN. Herein, we reveal how a hospital might use information gathered in a hospital registry of PNB outcomes to guide future quality enhancement efforts.MethodThis was an observational, prospective, and unicenter study of all peripheral nerve blocks done in the operating room since December 22, 2022. After studying the data collected by the existing registries worldwide, the anesthesiology research center at Taleghani Hospital developed a questionnaire that incorporated the varying parameters set forth by earlier research and registries. Parameters were documented for each patient.ResultsA total of 105 patients, were accrued from December 22, 2022, to July 23, 2023. The brachial plexus blocks namely axillary, infraclavicular, and popliteal blocks were the most frequently used PNBs, respectively. The indications that generated the greatest demand for PNBs were upper limb fractures, I&D, and amputation, respectively. 82.9% of blocks were conducted while patients were sedated employing systemic administration of sedatives. In this registry, there were no deaths or complications with sequelae. The median duration of hospitalization following admission to the hospital was 3 days. The mean patient satisfaction score was 9.46 out of 10.ConclusionOur analysis demonstrates the effectiveness, safety, and feasibility of peripheral nerve blocks in preoperative anesthesia. It is recommended to continue the registry and conduct additional studies to enhance our understanding of this procedure.

Hierarchical braking accurate control of electrohydraulic composite braking system for electric vehicles.

For the electrohydraulic composite braking system, the general total braking force calculation strategy frequently ignores the resist forces, thereby cannot track the braking intention of driver perfectly. Moreover, the torque allocation process reduces the control reliability and energy recovery effect. In this research, a novel hierarchical braking accurate control (HBAC) algorithm is designed to achieve both the control accuracy and the ideal energy recovery efficiency. It includes target calculation, parameter adjustment, and organization coordination levels. In the target calculation level, the resist forces such as air, tire roll resistances are considered to calculate the demanded-braking force accurately. In the parameter adjustment level, the ideal demand-braking force is constrained by the estimated road adhesion coefficient and the vertical load transfer. At the organization coordination level, the torque allocation process is omitted by applying a compensation control of the hydraulic braking torque. The simulation results indicated outstanding braking distances by the proposed HBAC are 111.5 m, 40.8 m, and 63.2 m under the varying adhesion, dry asphalt, and wet asphalt roads, respectively. Moreover, compared with the comparative control strategy, the energy recovery efficiency of HBAC is increased by 11.74 %, 6.67 %, and 8.4 % under these road conditions. Experimental implementation corroborates the effectiveness of proposed strategy.

Quantifying degradation in animal acoustic signals with the R package baRulho

Abstract Animal acoustic signals are shaped by selection to convey information based on their tempo, intensity, and frequency. However, sound signals degrade as they transmit over space and across physical obstacles (e.g., vegetation or infrastructure), which affects communication potential. Therefore, propagation experiments are designed to quantify changes in signal structure in a given habitat by broadcasting and re‐recording animal sounds at increasing distances. We introduce ‘baRulho’, an R package designed to simplify the implementation of sound propagation experiments. We highlight the package features with a case study testing the effects of habitat and acoustic structure on signal propagation, two common factors evaluated in such experiments. Synthesized sounds that varied in frequency, duration, and frequency and amplitude modulation were broadcast and re‐recorded at five increasing distances in open and closed understory at the Bosque de Tlalpan, Mexico City. With this data, we showcase baRulho's functions to prepare master sound files, annotate re‐recorded test sounds, as well as to calculate and visualize measures that quantify the degradation of acoustic signals in the time and frequency domain. Degradation measures in baRulho adequately quantified acoustic degradation, following predicted patterns of sound propagation in natural environments. Re‐recorded signals degraded less in open understory compared to closed understory, with higher‐frequency sounds exhibiting more degradation. Furthermore, frequency modulated sounds degraded to a greater extent than pure tones. The increased attenuation and reverberation observed in higher frequency sounds and closed habitats suggest that factors such as absorption and scattering by vegetation play significant roles in propagation patterns. The R package ‘baRulho’ provides an open‐source, user‐friendly suite of tools designed to facilitate the analysis of animal sound degradation. Notably, baRulho offers similar results to other sound analysis software but with significantly reduced processing time. Moreover, the package minimizes the potential for user error through automated test file annotation and verification procedures. We hope that baRulho can help enhance accessibility to propagation experiments within the research community, ultimately contributing to a deeper understanding of the ecological drivers of animal communication systems.

Tunable optical Kerr transmittance and structured light by a nanostructured TiO2 bilayer

The contrast in the third-order nonlinear optical properties exhibited by TiO2 nanosheets and TiO2 nanostructured thin films is reported. The effects of the particle morphology of the samples were characterized in order to evaluate their influence in the solid compounds. The implementation of a Z-scan experiment allows us to analyze the optical Kerr effect and the nonlinear optical absorption in the samples studied. A significant reverse saturable absorption and negative refractive index were measured in the TiO2 nanosheets, obtaining a switch in the sign of the nonlinear parameters for the TiO2 nanopowder sample irradiated by nanosecond pulses. Additionally, a vectorial two-wave mixing method was used to observe the evolution of the optical Kerr effect in the TiO2 thin films in tandem configurations proposed with potential applications related to structured light. A clear control in the angular momentum of light, dependent on the nanoscale morphology of the bilayer system, is highlighted. These results, together with the TiO2 versatility, could be very attractive for a handful of different all-optical devices integrated by considering tailored synthesis parameters.

Quantum machine learning with Adaptive Boson Sampling via post-selection

The implementation of large-scale universal quantum computation represents a challenging and ambitious task on the road to quantum processing of information. In recent years, an intermediate approach has been pursued to demonstrate quantum computational advantage via non-universal computational models. A relevant example for photonic platforms has been provided by the Boson Sampling paradigm and its variants, which are known to be computationally hard while requiring at the same time only the manipulation of the generated photonic resources via linear optics and detection. Beside quantum computational advantage demonstrations, a promising direction towards possibly useful applications can be found in the field of quantum machine learning, considering the currently almost unexplored intermediate scenario between non-adaptive linear optics and universal photonic quantum computation. Here, we report the experimental implementation of quantum machine learning protocols by adding adaptivity via post-selection to a Boson Sampling platform based on universal programmable photonic circuits fabricated via femtosecond laser writing. Our experimental results demonstrate that Adaptive Boson Sampling is a viable route towards dimension-enhanced quantum machine learning with linear optical devices.

Efficient optimisation of physical reservoir computers using only a delayed input

Reservoir computing is a machine learning algorithm for processing time dependent data which is well suited for experimental implementation. Tuning the hyperparameters of the reservoir is a time-consuming task that limits is applicability. Here we present an experimental validation of a recently proposed optimisation technique in which the reservoir receives both the input signal and a delayed version of the input signal. This augments the memory of the reservoir and improves its performance. It also simplifies the time-consuming task of hyperparameter tuning. The experimental system is an optoelectronic setup based on a fiber delay loop and a single nonlinear node. It is tested on several benchmark tasks and reservoir operating conditions. Our results demonstrate the effectiveness of the delayed input method for experimental implementation of reservoir computing systems.

A portable EEG signal acquisition system and a limited-electrode channel classification network for SSVEP

Brain-computer interfaces (BCIs) have garnered significant research attention, yet their complexity has hindered widespread adoption in daily life. Most current electroencephalography (EEG) systems rely on wet electrodes and numerous electrodes to enhance signal quality, making them impractical for everyday use. Portable and wearable devices offer a promising solution, but the limited number of electrodes in specific regions can lead to missing channels and reduced BCI performance. To overcome these challenges and enable better integration of BCI systems with external devices, this study developed an EEG signal acquisition platform (Gaitech BCI) based on the Robot Operating System (ROS) using a 10-channel dry electrode EEG device. Additionally, a multi-scale channel attention selection network based on the Squeeze-and-Excitation (SE) module (SEMSCS) is proposed to improve the classification performance of portable BCI devices with limited channels. Steady-state visual evoked potential (SSVEP) data were collected using the developed BCI system to evaluate both the system and network performance. Offline data from ten subjects were analyzed using within-subject and cross-subject experiments, along with ablation studies. The results demonstrated that the SEMSCS model achieved better classification performance than the comparative reference model, even with a limited number of channels. Additionally, the implementation of online experiments offers a rational solution for controlling external devices via BCI.

Quantum Mechanics in Plasmonic Nanocavities: from Theory to Applications

AbstractQuantum mechanical effects in plasmonic nanocavities have attracted strong interest in the last two decades, related to both their experimental realization and implementation in technological applications, and to the challenges that need to be overcome in their theoretical modeling. This review summarizes the basic theories of quantum plasmonics, its modeling strategies, and the material systems that support it. Particularly it is focused on recent progress in quantum plasmonics based on the nanoparticle‐on‐mirror (NPoM) structure, i.e., plasmonic nanoparticles separated from an underlying metallic substrate via an ultrathin spacer, which provides an elegant route toward cost‐effective fabrication of a large number of similar plasmonic cavities. A dramatic shift of research trends is seen from basic modeling to applications in nano‐optics, polaritonics, chemistry, and biosensing, gradually making the transition from fundamental, curiosity‐driven research to applied science.

Practical fractional-order terminal sliding-mode control for a class of continuous-time nonlinear systems

Terminal sliding-mode control (TSMC) has been studied and applied extensively in the last few years. This technique gives rise to a robust control with tunable finite-time convergence, providing a fast and accurate response in the presence of parameter uncertainties. In that sense, we present a closed-loop robust controller for a class of nonlinear systems using a terminal sliding-mode controller, with a novel fractional-order sliding surface. The motivation of this work is to consider a time-varying gain for the fractional-order sliding surface that is relatively small at the beginning of the regulation control task to reduce the amplitude of the control input and it increases near the final time to reduce the error in the steady state. Unlike using a constant gain in the conventional terminal sliding surface, the time-varying gain keeps the amplitude of the signal low and enhances the precision simultaneously. An extensive simulation study shows the performance of the proposed design. Finally, the experimental implementation of the fractional-order TSMC in a lightweight (90 g) two-degree-of-freedom manipulator is presented. The implementation used C++ programming language on a Raspberry Pi digital board and a chattering-free modification was presented to address the practical limitation of the actuators.

Dynamics of a single anisotropic particle under various resetting protocols

We study analytically the dynamics of an anisotropic particle subjected to different stochastic resetting schemes in two dimensions. The Brownian motion of shape-asymmetric particles in two dimensions results in anisotropic diffusion at short times, while the late-time transport is isotropic due to rotational diffusion. We show that the presence of orientational resetting promotes the anisotropy to late times. When the spatial and orientational degrees of freedom are reset, we find that a non-trivial spatial probability distribution emerges in the steady state that is determined by the initial orientation, particle asymmetry and the resetting rate. When only spatial degrees of freedom are reset while the orientational degree of freedom is allowed to evolve freely, the steady state is independent of the particle asymmetry. When only particle orientation is reset, the late-time probability density is given by a Gaussian with an effective diffusion tensor, including off-diagonal terms, determined by the resetting rate. Generally, the coupling between the translational and rotational degrees of freedom, when combined with stochastic resetting, gives rise to unique behavior at late times not present in the case of symmetric particles. Considering recent developments in experimental implementations of resetting, our results can be useful for the control of asymmetric colloids, for example in self-assembly processes.

Synthetic aperture X-ray ghost imaging with sub-micron pixel resolution.

Synthetic aperture X-ray ghost imaging (SAXGI) is proposed to achieve megapixel X-ray ghost imaging together with a reduced number of measurements. As the bucket detector array is artificially generated by post-pixel-binning of the images collected with the same detector as that in the reference arm, the unique advantages of SAXGI are not verified experimentally. In this paper, we developed a systematic solution of the experimental implementation of SAXGI, with the automatic interchange of 2× and 20× optical magnification of the detector for object and reference signal acquisition respectively, together with electronic pixel-binning of the detector. Taking the experimentally achieved 40×40 blocks as the bucket array in the object arm and addressing the challenge of image registration among the reference and object signals, we successfully achieved SAXGI imaging of 1960×1920 pixels with a pixel size of 0.325 µm. By developing a set of protocols improved in each part of the experiments, we can implement the data acquisition process of SAXGI in a few minutes, which is anticipated to facilitate the further application of the SAXGI method in related research fields.

Wave energy evolution and vortex dynamics induced by gap resonance between multiple floating rectangular structures

This study presents an experimental design and implementation aimed at investigating the processes of wave energy evolution and vortex generation and shedding under wave-induced gap resonance between multiple floating rectangular structures (MFRSs). A synchronized particle image velocimetry system, combined with an efficient data processing method, is adopted to study the wave energy evolution from the initial to the quasi-steady state. The validity of experiment was confirmed by published experimental and numerical data, regarding variations of resonant wave height vs dimensionless incident wave numbers and free surface elevations. The intrinsic nature of two distinct gap resonant frequencies was clarified through comprehensive analyses of the flow field and phase difference of the free surface elevation. The resonant characteristics, total wave energy dissipation, and the contributions of viscous dissipation from wall friction and flow separation around two gaps of MFRSs were estimated quantitatively. The Ω-criterion vortex identification method was selected to investigate vortex generation, shedding, and dissipation modes of MFRSs. The results indicate that the second resonant frequency in gap 1 is primarily induced by fluid motion oscillations in gap 2. A substantial portion of the incident wave energy, approximately 55.4%, is dissipated under gap resonance. The diameter of vortex structures at the fundamental resonant wave frequency in gap 1 is at least three times larger than that at the second resonant wave frequency. The energy accumulated by the water blockage effect of vortex structures significantly exceeds the energy dissipated by the increased vortex generation and shedding under wave-induced gap resonance.

Experimental implementation of an Algorithm for Real Time Compensation of Phase Current Sensors DC Offset in Field Oriented Controlled PMSM Drives

Experimental implementation of an Algorithm for Real Time Compensation of Phase Current Sensors DC Offset in Field Oriented Controlled PMSM Drives

Climate Diplomacy: Unlocking International Cooperation for a Sustainable Future

Climate diplomacy has become an essential mechanism for fostering international cooperation to combat the global crisis of climate change. This study explores its growth, successes, and challenges, offering understandings into its transformative journey from fragmented environmental determinations to a more cohesive and inclusive global context. Landmark agreements such as the Kyoto Protocol, Paris Agreement, and Glasgow Climate Pact have marked important milestones, driving progress toward global climate goals. However, modern experiments geopolitical tensions, economic disparities, and implementation gaps threaten the efficiency of these initiatives. The research highlights the essential role of international association in addressing transboundary climate issues. It postulates the need for just mechanisms of climate finance to enable the developing nations, and integrates science and technology for policy orientation and innovation. The study provides actionable strategies that tackle persistent barriers such as increasing transparency and trust through independent assessments, equitable technology sharing, and building on regional and subnational initiatives. It concludes that climate diplomacy has made considerable strides but needs sustained commitment and inclusive approaches to bridge the gaps in finance, trust, and implementation.

Optimasi Penggunaan Kembali Limbah Karbon Aktif Industri Vetsin Sebagai Biochar Menggunakan Taguchi Orthogonal Array L4

PT XY is a company producing vetsin in the food industry. The company makes extensive use of material resources for its industrial development, which has an impact on the environment. Waste-activated carbon is the result of the color absorption process of the solution. The problem is that the waste generated causes pollution to the company's environment and cannot be stored for long. The average carbon waste generated from January to December 2023 is 86.40 tonnes. Therefore, it is necessary to reuse activated carbon waste into biochar or carbon fertilizer. Processing strategy by conducting experiments using the Taguchi method. Problem identification with an approach that refers to the Responsible Waste Management Hierarchy, and limits the implementation of experiments to the principle of reuse. The Taguchi Orthogonal Array L4 method was chosen for the experimental design because it is more cost-effective than other DOEs and the signal noise is predictable. This research was conducted through experimental methods to know the effect of biochar planting media from activated carbon waste on the growth of kale plants (gr) and get optimal composition variations. As a result, an optimization design was obtained with wet carbon waste material, 25% biochar concentration, and bright light conditions, with an n-gain value of 4.49 resulting in a high improvement category. Comparison of biochar quality with Charcoal Powder from Workplant Store by SNI 06-3730-1995 standard. In biochar products from activated carbon waste, there is a glutamate content of 0.345 g/dL which is a good amino acid for plant growth.

Experimental implementation of a chaos-based video encryption using visible light communication technology

Experimental implementation of a chaos-based video encryption using visible light communication technology

Experimental and computational evaluation of knee implant wear and creep under in vivo and ISO boundary conditions

Abstract Background Experimental knee implant wear testing according to ISO 14243 is a standard procedure, but it inherently possesses limitations for preclinical evaluations due to extended testing periods and costly infrastructure. In an effort to overcome these limitations, we hereby develop and experimentally validate a finite-element (FE)-based algorithm, including a novel cross-shear and contact pressure dependent wear and creep model, and apply it towards understanding the sensitivity of wear outcomes to the applied boundary conditions. Methods Specifically, we investigated the application of in vivo data for level walking from the publicly available “Stan” data set, which contains single representative tibiofemoral loads and kinematics derived from in vivo measurements of six subjects, and compared wear outcomes against those obtained using the ISO standard boundary conditions. To provide validation of the numerical models, this comparison was reproduced experimentally on a six-station knee wear simulator over 5 million cycles, testing the same implant Stan’s data was obtained from. Results Experimental implementation of Stan’s boundary conditions in displacement control resulted in approximately three times higher wear rates (4.4 vs. 1.6 mm3 per million cycles) and a more anterior wear pattern compared to the ISO standard in force control. While a force-controlled ISO FE model was unable to reproduce the bench test kinematics, and thus wear rate, due to a necessarily simplified representation of the simulator machine, similar but displacement-controlled FE models accurately predicted the laboratory wear tests for both ISO and Stan boundary conditions. The credibility of the in silico wear and creep model was further established per the ASME V&V-40 standard. Conclusions The FE wear model is suitable for supporting future patient-specific models and development of novel implant designs. Incorporating the Stan data set alongside ISO boundary conditions emphasized the value of using measured kinematics in displacement control for reliably replicating in vivo joint mechanics in wear simulation. Future work should focus on expanding the range of daily activities simulated and addressing model sensitivity to contact mechanics to further enhance predictive accuracy.

Nonlinear Adaptive Optimal Control Design and Implementation for Trajectory Tracking of Four-Wheeled Mecanum Mobile Robots

This study proposes a nonlinear adaptive optimal control method, the adaptive H2 control method, applied to the trajectory tracking problem of the wheeled mobile robot (WMR) with four-wheel mecanum wheels. From the perspective of solving mathematical problems, finding an analytical adaptive control solution that satisfies the adaptive H2 performance criterion for the trajectory tracking problem of the WMR with four-wheel mecanum wheels is an extremely challenging task due to the high complexity of the dynamic system. To analytically derive the control law and adaptive control law for this trajectory tracking problem, a proportional-derivative (PD) type transformation is employed to formalize the trajectory tracking error dynamics between the WMR and the desired trajectory (DT). Based on an in-depth analysis of the trajectory tracking error dynamics, a closed-form adaptive control law is analytically derived from the highly complex nonlinear dynamic system equations. This control law provides a solution to the trajectory tracking problem of the WMR while satisfying the adaptive H2 performance criterion. The proposed adaptive nonlinear control method offers a simple control structure and advantages such as improved energy efficiency. Finally, simulations and experimental implementations were conducted to verify the performance of the proposed adaptive H2 control method and the H2 control method in tracking the DT. The results demonstrate that, compared to the H2 control method, the adaptive H2 control method exhibits superior trajectory tracking performance, particularly in the presence of significant model uncertainties.