Arbitrary System Research Articles

Typical bipartite steerability and generalized local quantum measurements

Recently proposed correlation-matrix-based sufficient conditions for bipartite steerability from Alice to Bob for arbitrary measurements are applied to local informationally complete positive operator valued measures (POVMs) of the (N,M)-type. These POVMs include a large class of local generalized measurements of current interest [Siudzińska K 2022 Phys. Rev. A 105 042209]. It is shown that the trace norm of correlation matrices with local (N,M)-POVMs is proportional to that of local orthonormal hermitian operator bases (LOOs). This implies that all types of informationally complete (N,M)-POVMs are equally powerful in detecting bipartite steerability from Alice to Bob and, in addition, they are as powerful as LOOs. In order to explore the typicality of steering numerical calculations of lower bounds on Euclidean volume ratios between steerable bipartite quantum states from Alice to Bob and all quantum states are determined with the help of a hit-and-run Monte-Carlo algorithm. These results demonstrate that with the single exception of two qubits this correlation-matrix-based sufficient condition significantly underestimates these volume ratios. These results are also compared to a recently proposed method that determines bipartite steerability from Alice’s qubit to Bob’s arbitrary dimensional quantum system by bipartite entanglement detection. It is demonstrated that in general this method is significantly more effective in detecting typical steerability provided non local entanglement detection methods are used which transcend local measurements.

Generalized Quantum Measurements on a Higher-Dimensional System via Quantum Walks.

Quantum measurements play a fundamental role in quantum mechanics. Especially, generalized quantum measurements provide a powerful and versatile tool to extract information from quantum systems. However, how to realize them on an arbitrary higher-dimensional quantum system remains a challenging task. Here we propose a simple recipe for the implementation of a general positive-operator valued measurement (POVM) on a higher-dimensional quantum system via a one-dimensional discrete-time quantum walk with a two-dimensional coin. Furthermore, using single photons and linear optics, we realize experimentally a symmetric, informationally complete (SIC) POVM on a three-dimensional system with high fidelity. As an application, we realize a qutrit state tomography with SIC-POVM and confirm that the infidelity scaling achieved by the qutrit SIC-POVM is as good as that based on mutually unbiased bases. Our study paves the way to explore physics and information in higher-dimensional quantum systems and finds applications in various quantum information processing tasks that rely on generalized quantum measurements.

Detecting multipartite entanglement via complete orthogonal basis

We study genuine tripartite entanglement and multipartite entanglement in arbitrary n-partite quantum systems based on complete orthogonal basis (COB). While the usual Bloch representation of a density matrix uses three types of generators, the density matrix with COB operators has one uniformed type of generators which may simplify related computations. We take the advantage of this simplicity to derive useful and operational criteria to detect genuine tripartite entanglement and multipartite entanglement. We first convert the general states to simpler forms by using the relationship between general symmetric informationally complete measurements and COB. Then we derive an operational criteria to detect genuine tripartite entanglement. We study multipartite entanglement in arbitrary dimensional multipartite systems. By providing detailed examples, we demonstrate that our criteria can detect more genuine entangled and multipartite entangled states than the previously existing criteria.

Flexible and High-Gain DOFS Deconvolution Based on Data-Driven Denoising Prior

Spatial resolution is an essential parameter for distributed optical fiber sensing (DOFS). Deconvolution is a promising solution to improve spatial resolution because of its good universality and ability to restore infinitely high spatial resolution in theory. However, conventional iterative deconvolution algorithms require manually designed priors, which makes it difficult to restore the signal accurately. Although end-to-end methods based on artificial neural networks provide more accurate results based on data-driven priors, a neural network can only be applied to data with similar characteristics to its training data. For systems with different parameters, the neural network needs to be retrained or fine-tuned, which is time and computational resource consuming. Here, we employ a new deconvolution method for DOFS based on half-quadratic splitting and denoising neural networks that exploits the advantages of both iterative and machine learning methods. Besides, we propose a method to calculate the deconvolution gain to evaluate the deconvolution performance quantitatively. In an experiment with 10 deconvolution ratios, the deconvolution gain of the employed method is 15.8 dB, while that of a conventional iterative method and an end-to-end machine learning method are 7.9 dB and 15 dB, respectively. Moreover, this new deconvolution method can be adapted to data with arbitrary system parameters, making it more flexible than end-to-end neural networks in practical applications.

Mapping Molecular Hamiltonians into Hamiltonians of Modular cQED Processors.

We introduce a general method based on the operators of the Dyson-Masleev transformation to map the Hamiltonian of an arbitrary model system into the Hamiltonian of a circuit Quantum Electrodynamics (cQED) processor. Furthermore, we introduce a modular approach to programming a cQED processor with components corresponding to the mapping Hamiltonian. The method is illustrated as applied to quantum dynamics simulations of the Fenna-Matthews-Olson (FMO) complex and the spin-boson model of charge transfer. Beyond applications to molecular Hamiltonians, the mapping provides a general approach to implement any unitary operator in terms of a sequence of unitary transformations corresponding to powers of creation and annihilation operators of a single bosonic mode in a cQED processor.

Physics-Informed Long-Short-Term Memory Neural Network for Parameters Estimation of Nonlinear Systems

This paper proposes a physics-informed long-short-term memory neural network optimisation method to estimate all parameters of an arbitrary nonlinear system initialised using any initial conditions. Although the technique is applicable for parameters' estimation of any nonlinear system, in this paper, two well-known chaotic systems are considered with different initial conditions. The three-dimensional Lorenz chaotic system and the four-dimensional Rössler hyperchaotic system are considered. The Lorenz system exhibits stable, chaotic and periodic behaviours for some sets of parameters. Thus, different sets of parameters of the Lorenz system are individually estimated, leading to stable, periodic and chaotic behaviours. In 10000 epochs, the stable and periodic parameters' estimation accuracy is more than 99%; in 15000 epochs, chaotic parameters' estimation accuracy is more than 99%. Upto same epochs, physics-informed neural network is employed for parameter estimation of stable, periodic and chaotic behaviours of the Lorenz system. The comparison results of estimated parameters are shown with dataset obtained using ode45. Next, Circuit realisation of the Lorenz system is done and the dataset is obtained using multisim circuit simulation for stable, chaotic and periodic behaviour. The proposed physics-informed long-short-term memory neural network is used to obtain parameters from the practical data. Then, the estimation of the Lorenz system with a continuum variation of parameters' sets from stable to chaotic to stable behaviours is successfully achieved using the proposed physics-informed long-short-term memory neural network. Finally, the hyperchaotic Rössler system parameters are successfully estimated using the proposed technique with more than 99% accuracy in 20000 epochs.

Geometric approach to nonequilibrium hasty shortcuts.

Complex and even non-monotonic responses to external control can be found in many thermodynamic systems. In such systems, nonequilibrium shortcuts can rapidly drive the system from an initial state to a desired final state. One example is the Mpemba effect, where preheating a system allows it to cool faster. We present nonequilibrium hasty shortcuts-externally controlled temporal protocols that rapidly steer a system from an initial steady state to a desired final steady state. The term "hasty" indicates that the shortcut only involves fast dynamics without relying on slow relaxations. We provide a geometric analysis of such shortcuts in the space of probability distributions by using timescale separation and eigenmode decomposition. We further identify the necessary and sufficient condition for the existence of nonequilibrium hasty shortcuts in an arbitrary system. The geometric analysis within the probability space sheds light on the possible features of a system that can lead to hasty shortcuts, which can be classified into different categories based on their temporal pattern. We also find that the Mpemba-effect-like shortcuts only constitute a small fraction of the diverse categories of hasty shortcuts. This theory is validated and illustrated numerically in the self-assembly model inspired by viral capsid assembly processes.

Modelling hydrogen storage and filling systems: A dynamic and customizable toolkit

Hydrogen plays a vital role in decarbonizing the mobility sector. With the number of hydrogen vehicles expected to drastically increase, a network of refuelling stations needs to be built to keep up with the hydrogen demand. However, further research and development on hydrogen refuelling infrastructure, storage and standardization is required to overcome technical and economic barriers. Simulation tools can reduce time and costs during the design phase, but existing models do not fully support calculations of complete and arbitrary system layouts. Therefore, a flexible simulation toolbox for rapid investigations of hydrogen refuelling and extraction processes as well as development of refuelling infrastructure, vehicle tank systems and refuelling protocols for non-standardized applications was developed. Our model library, H2VPATT, comprises of typical components found in refuelling infrastructure. The key component is the hydrogen tank model. The simulation model was successfully validated with measurement data from refuelling tests of a 320 l type III tank.

QuDPy: A Python-based tool for computing ultrafast non-linear optical responses

Nonlinear Optical Spectroscopy is a well-developed field with theoretical and experimental advances that have benefited multiple disciplines, including chemistry, biology, and physics. However, for the accurate interpretation of the corresponding multi-dimensional spectra, there is a need for precise quantum dynamical simulations based on model Hamiltonians. In this article, we present the initial release of our code, QuDPy (Quantum Dynamics in Python), which provides a robust numerical platform for performing quantum dynamics simulations based on model systems, including open quantum systems. A distinguishing feature of our approach is the ability to specify various high-order optical response pathways in the form of double-sided Feynman diagrams through a straightforward input syntax. This syntax outlines the time-ordering of ket-sided or bra-sided optical interactions acting on the time-evolving density matrix of the system. We utilize the quantum dynamics capabilities of QuTip to simulate the spectral response of complex systems, allowing us to compute virtually any n-th order optical response of the model system. To illustrate the utility of our approach, we provide a series of example calculations. Program summaryProgram Title:QuDPyCPC Library link to program files:https://doi.org/10.17632/5xm9pm24cz.1Developer's repository link:https://github.com/sa-shah/QuDPyLicensing provisions: MIT LicenseProgramming language: Python (v3.7)Supplementary material: Available as Google Colab Files.Example 1: https://tinyurl.com/y3j5jmmrExample 2: https://tinyurl.com/37vwntn5External packages:•QuTip (v.4.7) and dependencies i.e. Numpy, Matplotlib (https://qutip.org/)•UFSS Automatic Diagram Generator (https://github.com/peterarose/ufss)Nature of problem: Accurate quantum simulations of complex systems are required in order to understand and interpret multi-dimensional ultrafast spectroscopic signals. This code provides an open-source/multi-platform method that facilitates the generation of higher-order non-linear optical responses for an arbitrary molecular or material system given a model input Hamiltonian and bath model.Solution method: We use the double-sided Feynman diagram method [1, 2] to generate (symbolically) a set of response functions corresponding to the nth order non-linear response of the system to a series of laser pulses using the UFSS package [3] We then perform a series of accurate quantum dynamics calculations using the QuTip package [4] to generate the numerical response and spectra which correspond to specific experimental conditions.

Predicer: abstract stochastic optimisation model framework for multi-market operation

An open-source modelling framework Predicer, standing for Predictive Decider, for multi-market day-ahead market operation purposes is described in this paper. The Predicer model uses scenario-based stochastic optimisation to obtain decision variables and bid matrixes for energy and reserve markets by maximising the risk-adjusted expected value of the profit during the model time frame. The modelled energy system structure is abstract, that is, based on basic elements such as nodes representing different energy types and processes representing flows between nodes. The abstract model structure enables user to construct arbitrary energy systems and define links between assets, commodities, energy markets and reserve markets. Predicer model can include properties such as unit ramp rates, online units, dynamic energy storages, market realisation and market bidding requirements. The aggregation of unit-based energy and reserve opportunities into a virtual power plant allows the asset owner to make optimized portfolio-level bids for different market products. The model scenarios consist of user defined forecasts for market prices, renewable energy supply, energy demand and other system related time series. Predicer is implemented in Julia programming language and uses the JuMP optimisation package.

Caracal: A Versatile Ring Polymer Molecular Dynamics Simulation Package.

A new open-source program package named Caracal covering simulations of molecular systems with ring polymer molecular dynamics (RPMD) is presented. It combines a powerful RPMD implementation including chemical reaction rate calculations and biased periodic and nonperiodic samplings with a collection of easy to set up potential energy surface (PES) methodologies, thus delivering an all-inclusive approach. Most implemented PESs are based on the QMDFF and EVB-QMDFF methods. Where the quantum mechanically derived force field (QMDFF) can be set up for an arbitrary molecular system in a black-box fashion, the empirical valence bond (EVB)-QMDFF connects two QMDFFs and is able to represent the PES of a chemical reaction. With our previously published flavors of this composite method, PESs for almost arbitrary gas phase thermal ground state reactions can be set up. Given an optimized reaction path, the mechanism of the reaction can be classified and RPMD rate constants can be obtained via umbrella sampling and recrossing calculations on an EVB-QMDFF PES. Further, QMDFFs can be polymerized for the description of liquid systems. In this paper, the internal structure as well as the handling philosophy of Caracal are outlined. Further, examples of the different possible kinds of calculations are given.

Properties of the weakly-bound (1,1)-states and rotationally excited (2,0)-states in the muonic molecular and ions

Total energies and other bound state properties of the weakly-bound (1,1)-states and rotationally excited (2,0)-states in the three-body muonic molecular and ions are determined to high numerical accuracy and investigated. Our current numerical accuracy achieved for the total and binding energies of the weakly-bound (1,1)-states in the both and ions significantly exceeds similar accuracy obtained in earlier computations of these weakly-bound states in these two ions. The bound state properties of the weakly-bound (1,1)-states and (2,0)-states in the and muonic ions have never been determined to high accuracy in earlier studies. We also briefly discuss the current status of muon-catalysed nuclear fusion and develop the new universal variational expansion which can be used for extremely accurate bound state calculations of arbitrary three-body systems, including the truly adiabatic H ion and close systems.

Linear Response Theory of Evolved Metabolic Systems.

Predicting cellular metabolic states is a central problem in biophysics. Conventional approaches, however, sensitively depend on the microscopic details of individual metabolic systems. In this Letter, we derived a universal linear relationship between the metabolic responses against nutrient conditions and metabolic inhibition, with the aid of a microeconomic theory. The relationship holds in arbitrary metabolic systems as long as the law of mass conservation stands, as supported by extensive numerical calculations. It offers quantitative predictions without prior knowledge of systems.

On the Existence of the Conditionally Linear Integral in Conservative Holonomic Systems with Two Degrees of Freedom

For the Lagrange equations of the 2nd kind the problem on the existence of the conditionally linear in the velocities integral, which possesses the property that its total time derivative is identically proportional to the integral itself, is considered. The Lagrange function is assumed to be given in arbitrary generalized coordinates. The conditions for the existence of such integral are reduced to the study of the compatibility of two equations in partial derivatives of the 2nd order for one unknown function of two independent arguments. These equations are written in the invariant form in an arbitrary system of generalized coordinates and the problem is transformed to the investigation of the set of Pfaffian equations.

Demonstration of a Bosonic Quantum Classifier with Data Reuploading.

In a single qubit system, a universal quantum classifier can be realized using the data reuploading technique. In this study, we propose a new quantum classifier applying this technique to bosonic systems and successfully demonstrate it using a silicon-based photonic integrated circuit. We established a theory of quantum machine learning algorithm applicable to bosonic systems and implemented a programmable optical circuit combined with an interferometer. Learning and classification using part of the implemented optical quantum circuit with uncorrelated two photons resulted in a classification with a success probability of 94±0.8% in the proof of principle experiment. As this method can be applied to an arbitrary two-mode N-photon system, further development of optical quantum classifiers, such as extensions to quantum entangled and multiphoton states, is expected in the future.

Time Base Generator-Based Practical Predefined-Time Stabilization of High-Order Systems With Unknown Disturbance

This paper investigates a predefined-time stabilization problem for a high-order integrator chain system with an unknown disturbance by using a time base generator (TBG) method. Until now it is still a challenge to realize the TBG based predefined-time stabilization for high-order systems. In this paper, a novel TBG function is constructed for a high-order integrator system and a nonlinear coordinate transformation is proposed to facilitate the design of the predefined-time controller. The feature of this TBG function is that it is smooth and applicable to arbitrary order systems. Then the practical predefined-time stability of the closed-loop system is analyzed under the proposed TBG based controller when an unknown disturbance exists in the system. Furthermore, the settling time can be preset arbitrarily, and thus is independent of the system’s initial condition. Finally, some numerical examples are presented to validate the effectiveness of the proposed TBG based control strategy.

Code Mixing dalam Novel Negeri Lima Menara

Language is not only a set of languages, but also serves a social function. Sapir in Lyons (1982: 3) says that language is used by humans to communicate, express emotions and desires through various symbols. While Wardhaugh added that language is an arbitrary system which basically has a function as a tool for communicating. This study aims to determine code mixing in the novel language. This type of research method used is qualitative research. The method used is descriptive method, which is a research method that describes data starting from the data collection stage, data compilation, accompanied by data analysis and interpretation. In this study, the type of data analyzed using written data. The data source in this study is a novel entitled Negeri Lima Menara by A. Fuadi. Data was collected by examining data from data sources using the basic method of observation, namely by observing the form of code mixing contained in the novel in the form of sentences and followed by the method of recording data from previously observed data. Then the researcher analyzes the form of code mixing contained in the novel and concludes the results obtained. Based on the results of the analysis of the collected data, it was concluded that the incident of mixing the Minang language code into Indonesian, Javanese into Surabaya dialect into Indonesian, Sundanese into Indonesian, Arabic into Indonesian, and English into Indonesian. The sociolinguistic meaning contained in the Negeri Lima Menara novel is the meaning of intimacy and is related to kinship culture in communicating in a multilingual society which is often used in communicating within family, friends, and Islamic boarding schools. Keywords: language, code mixing , negeri lima menara

Speeding up qubit control with bipolar single-flux-quantum pulse sequences

The development of quantum computers based on superconductors requires the improvement of the qubit state control approach aimed at the increase of the hardware energy efficiency. A promising solution to this problem is the use of superconducting digital circuits operating with single-flux-quantum (SFQ) pulses, moving the qubit control system into the cold chamber. However, the qubit gate time under SFQ control is still longer than under conventional microwave driving. Here we introduce the bipolar SFQ pulse control based on ternary pulse sequences. We also develop a robust optimization algorithm for finding a sequence structure that minimizes the leakage of the transmon qubit state from the computational subspace. We show that the appropriate sequence can be found for arbitrary system parameters from the practical range. The proposed bipolar SFQ control reduces a single qubit gate time by halve compared to nowadays unipolar SFQ technique, while maintaining the gate fidelity over 99.99%.

Method for Using IMU-Based Experimental Motion Data in BVH Format for Musculoskeletal Simulations via OpenSim

Biomechanical simulation allows for in silico estimations of biomechanical parameters such as muscle, joint and ligament forces. Experimental kinematic measurements are a prerequisite for musculoskeletal simulations using the inverse kinematics approach. Marker-based optical motion capture systems are frequently used to collect this motion data. As an alternative, IMU-based motion capture systems can be used. These systems allow flexible motion collection without nearly any restriction regarding the environment. However, one limitation with these systems is that there is no universal way to transfer IMU data from arbitrary full-body IMU measurement systems into musculoskeletal simulation software such as OpenSim. Thus, the objective of this study was to enable the transfer of collected motion data, stored as a BVH file, to OpenSim 4.4 to visualize and analyse the motion using musculoskeletal models. By using the concept of virtual markers, the motion saved in the BVH file is transferred to a musculoskeletal model. An experimental study with three participants was conducted to verify our method’s performance. Results show that the present method is capable of (1) transferring body dimensions saved in the BVH file to a generic musculoskeletal model and (2) correctly transferring the motion data saved in the BVH file to a musculoskeletal model in OpenSim 4.4.

Invariant manifold growth formula in cylindrical coordinates and its application for magnetically confined fusion

For three-dimensional vector fields, the governing formula of invariant manifolds grown from a hyperbolic cycle is given in cylindrical coordinates. The initial growth directions depend on the Jacobians of Poincaré map on that cycle, for which an evolution formula is deduced to reveal the relationship among Jacobians of different Poincaré sections. The evolution formula also applies to cycles in arbitrary finite n-dimensional autonomous continuous-time dynamical systems. Non-Möbiusian/Möbiusian saddle cycles and a dummy X-cycle are constructed analytically as demonstration. A real-world numeric example of analyzing a magnetic field timeslice on EAST is presented.