Dipole Model Research Articles

Efficient Bayesian inference and model selection for continuous gravitational waves in pulsar timing array data

Abstract Finding and characterizing gravitational waves from individual supermassive black hole binaries is a central goal of pulsar timing array experiments, which will require analysis methods that can be efficient on our rapidly growing datasets. Here we present a novel approach built on three key elements: (i) precalculating and interpolating expensive matrix operations; (ii) semi-analytically marginalizing over the gravitational-wave phase at the pulsars; (iii) numerically marginalizing over the pulsar distance uncertainties. With these improvements the recent NANOGrav 15 yr dataset can be analyzed in minutes after an O ( 1 h ) setup phase, instead of an analysis taking days–weeks with previous methods. The same setup can be used to efficiently analyze the dataset under any sinusoidal deterministic model. In particular, this will aid testing the binary hypothesis by allowing for efficient analysis of competing models (e.g. incoherent, monopolar, or dipolar sine wave model) and scrambled datasets for false alarm studies. The same setup can be updated in minutes for new realizations of the data, which enables large simulation studies.

A Novel Defect Quantification Method Utilizing Multi-Sensor Magnetic Flux Leakage Signal Fusion

In the assessment of pipeline integrity using magnetic flux leakage (MFL) detection, it is crucial to quantify defects accurately and efficiently using MFL signals. However, in complex detection environments, traditional defect inversion methods exhibit low quantification accuracy and efficiency due to the complexity of their algorithms or excessive reliance on a priori knowledge and expert experience. To address these issues, this study presents a novel defect quantification method based on multi-sensor signal fusion (MSSF). The method employs a multi-sensor probe to fuse the MFL signals under multiple lift-off values, enhancing the diversity of defect information. This enables defect-opening profile recognition using the characteristic approximation approach (CAA). Subsequently, the MSSF method is based on a 3D magnetic dipole model and integrates the structural features of multi-sensor probes to develop an algorithm. This algorithm iteratively determines the defect depth at multiple data acquisition points within the defect region to obtain the maximum defect depth. The feasibility of the MSSF quantification method is validated through finite element simulation and physical experiments. The results demonstrate that the proposed method achieves accurate defect quantification while enhancing efficiency, with the number of iterations for each defect depth calculation point consistently requiring fewer than 15 iterations. For rectangular metal loss, perforation, and conical defects, quantification errors are less than 10%, meeting practical inspection requirements.

A passive-tuned damper based on magnetorheological porous fabric composite

Abstract This paper proposes a novel passive-tuned magnetorheological (PTMR) damper based on developed magnetorheological (MR) porous fabric composite, in which the damping force is tuned by a permanent magnet (PM). Firstly, the influences of the porous fiber structure of composite on the suspended phase are considered, and a continuous constitutive model based on the dipole model is proposed for the first time, which can accurately predict its rheological properties. Subsequently, a stable passive damper for special conditions is designed, and the unique design concept is to achieve completely different damping characteristics for different application scenarios by adjusting the position of the PM relative to the magnetic circuit. The experimental results show that the damping force is relatively stable under specific condition, and can be adjusted within the range of 16.8–77.4 N, with a dynamic range of about 4.6. Moreover, the PTMR damper can exhibit unidirectional negative stiffness characteristic by adjusting the PM to a specific position. The PTMR damper has stable vibration reduction performance, wide dynamic range, and compact structure, which can be comparable to some conventional MR dampers.

Optical pump magnetometers parametric correction method based on three-axis coil arrays

Optical pump magnetometers (OPMs), based on the SERF principle, are increasingly prevalent in biomagnetic field detection and localization studies. However, cross-axis crosstalk is an unavoidable consequence of the non-ideal factors introduced during the development of the sensor array, whether during the initial design or manufacturing process. This study introduce a novel method to compensate for cross-axis crosstalk by a set of three-axis coils.The gain matrix of each sensor in an OPM array is calibrated by the magnetic field generated by the activation of the three-axis coils. The results showed that the correlation coefficients between the corrected coil distribution field measurements and the true values improved substantially, exceeding 0.99. Similarly, the similarity between the forward-field simulation and the measured results for the localization of a physical model of a current dipole improved significantly, from 0.78 to 0.96. This work presents the first report of the simultaneous calibration of a large OPM array comprising 64 OPMs. The suppression of cross-axis crosstalk errors improves the sensor measurement accuracy and the consistency of the array. This method is expected to further improve the accuracy of OPM array-based source localization.

Massive White Dwarfs in the 100 pc Sample: Magnetism, Rotation, Pulsations, and the Merger Fraction

We present a detailed model atmosphere analysis of massive white dwarfs with M > 0.9 M ⊙ and T eff ≥ 11,000 K in the Montreal White Dwarf Database 100 pc sample and the Pan-STARRS footprint. We obtained follow-up optical spectroscopy of 109 objects with no previous spectral classification in the literature. Our spectroscopic follow-up is now complete for all 204 objects in the sample. We find 118 normal DA white dwarfs, including 45 massive DAs near the ZZ Ceti instability strip. There are no normal massive DBs: the six DBs in the sample are strongly magnetic and/or rapidly rotating. There are 20 massive DQ white dwarfs in our sample, and all are found in the crystallization sequence. In addition, 66 targets are magnetic (32% of the sample). We use magnetic white dwarf atmosphere models to constrain the field strength and geometry using offset dipole models. We also use magnetism, kinematics, and rotation measurements to constrain the fraction of merger remnant candidates among this population. The merger fraction of this sample increases from 25% for 0.9–1 M ⊙ white dwarfs to 49% for 1.2–1.3 M ⊙. However, this fraction is as high as 78−7+4 % for 1.1–1.2 M ⊙ white dwarfs. Previous works have demonstrated that 5%–9% of high-mass white dwarfs stop cooling for ∼8 Gyr due to the 22Ne distillation process, which leads to an overdensity of Q-branch stars in the solar neighborhood. We demonstrate that the overabundance of the merger remnant candidates in our sample is likely due to the same process.

MEG in MRI-Negative Patients with Focal Epilepsy.

To review the evidence on the clinical value of magnetic source imaging (MSI) in patients with refractory focal epilepsy without evidence for an epileptogenic lesion on magnetic resonance imaging ("MRI-negative" or "non-lesional MRI"). We conducted a systematic literature search on PUBMED, which was extended by researchrabbit.ai using predefined criteria to identify studies that applied MSI in MRI-negative patients with epilepsy. We extracted data on patient characteristics, MSI methods, localization results, surgical outcomes, and correlation with other modalities. We included 23 studies with a total of 512 non-lesional epilepsy patients who underwent MSI. Most studies used equivalent current dipole (ECD) models to estimate the sources of interictal epileptic discharges (IEDs). MEG detected IEDs in 32-100% of patients. MSI results were concordant with other modalities, such as EEG, PET, and SPECT, in 3892% of cases. If MSI concordant surgery was performed, 52-89% of patients achieved seizure freedom. MSI contributed to the decision-making process in 28-75% of cases and altered the surgical plan in 5-33% of cases. MSI is a valuable diagnostic tool for MRI-negative patients with epilepsy, as it can detect and localize IEDs with high accuracy and sensitivity, and provides useful information for surgical planning and predicts outcomes. MSI can also complement and refine the results of other modalities, such as EEG and PET, and optimize the use of invasive recordings. MSI should be considered as part of the presurgical evaluation, especially in patients with non-lesional refractory epilepsy.

Study of Noise Reduction and Identification of Internal Damage Signals in Wire Ropes

Mining wire rope, a frequently used load-bearing element, suffers various forms of damage over extended periods of operation. Damage occurring within the wire rope, which is not visible to the naked eye and is difficult to detect accurately with current technology, is of particular concern. Consequently, the identification of internal damage assumes paramount importance in ensuring mine safety. This study proposes a wire rope internal damage noise reduction and identification method, first of all, through a three-dimensional magnetic dipole model to achieve the detection and analysis of the internal damage of the wire rope. Simultaneously, a sensor system capable of accurately detecting the internal damage of wire rope is developed and validated through experimentation. A novel approach is proposed to address the noise reduction issue in the design process. This approach utilizes a particle swarm optimization variational modal decomposition method to enhance the signal-to-noise ratio. Additionally, a dual-attention mode, which combines channel attention and spatial attention, is integrated into the CNN-GRU network model. This network model is specifically designed for the detection of internal damage in steel wire ropes. The proposed method successfully achieves quantitative identification of internal damage in steel wire ropes. The experimental findings demonstrate that this approach is capable of efficiently detecting internal damage in wire rope and possesses the capacity to quantitatively identify such damage, enabling adaptive identification of wire rope.

A new method for calculating the electric field distribution in particle-particle rotating systems

In the applied electric field, the behavioral characteristic which occurs in particle-particle systems always are used in dielectric insulation, and nanomaterials regulation, among which is the key to correctly compute the electric field. Because the dipole model without fully considering the particle interactions so that has defects in computing in some cases. This study introduced the mutual-coupling dipole offset distance τ used to describe the degree of inter-particle interaction, the analytical expression of the mutual-coupling dipole moment under the two types of the electric field is obtained, respectively. An original model is established, and by comparison with the finite element method, it is found that even when D = 0.1R and εpp/εf=25, the proposed model can describe the inter-particle interaction effectively, and its computational precision better than that of the classical model, which can realize the accurate computation of the electric field distribution around the particle-particle rotating system.

D meson production in p+Pb collisions with the analytical transverse momentum distribution from the color dipole models* *Supported by the National Natural Science Foundation of China Joint for Large Scientific Units (U1832120), the Hebei Province Outstanding Youth Fund (A2020210012), the S&T Program of Hebei (Grant No. 236Z4601G), and the Scientific Research Foundation for the Introducing Returned Overseas Chinese Scholars of

D meson production in proton–lead (p+Pb) collisions is globally investigated within the color dipole framework. To simplify the Fourier transform, the analytical transverse momentum distribution functions extracted from different color dipole models are used. With the Glauber–Gribov method, the impact parameter dependence is considered for the nuclear modification of the gluon density. We obtain from comparison with recent experimental data from the LHCb and ALICE Collaborations that the theoretical results from the Kovchegov, Lu and Rezaeian (KLR) model are in good agreement with the experimental data at small P T, and the results from the Golec–Biernat–Wüsthoff (GBW) and Bartels, Golec-Biernat and Kowalski (BGK) model are reasonable at all rapidity bins. Then, the influence of the initial-state energy loss effect on D meson production in p+Pb collisions is analyzed. A clear reduction of the nuclear modification factor is shown at backward rapidity. Finally, the predictive results for D0 and D+ production differential cross section versus rapidity (Y) in p+Pb collisions are given.

Machine learning classification of permeable conducting spheres in air and seawater using electromagnetic pulses

Abstract This paper presents machine learning classification on simulated data of permeable conducting spheres in air and seawater irradiated by low frequency electromagnetic pulses. Classification accuracy greater than 90% was achieved. The simulated data were generated using an analytical model of a magnetic dipole in air and seawater placed 1.5–3.5 m above the center of the sphere in 50 cm increments. The spheres had radii of 40 cm and 50 cm and were of permeable materials, such as steel, and non-permeable materials, such as aluminum. A series RL circuit was analytically modeled as the transmitter coil, and an RLC circuit as the receiver coil. Additive white Gaussian noise was added to the simulated data to test the robustness of the machine learning algorithms to noise. Multiple machine learning algorithms were used for classification including a perceptron and multiclass logistic regression, which are linear models, and a neural network, 1D convolutional neural network (CNN), and 2D CNN, which are nonlinear models. Feature maps are plotted for the CNNs and provide explainability of the salient parts of the time signature and spectrogram data used for classification. The pulses investigated, which expand the literature, include a two-sided decaying exponential, Heaviside step-off, triangular, Gaussian, rectangular, modulated Gaussian, raised cosine, and rectangular down-chirp. Propagation effects, including dispersion and frequency dependent attenuation, are encapsulated by the analytical model, which was verified using finite element modeling. The results in this paper show that machine learning methods are a viable alternative to inversion of electromagnetic induction (EMI) data for metallic sphere classification, with the advantage of real-time classification without the use of a physics-based model. The nonlinear machine learning algorithms used in this work were able to accurately classify metallic spheres in seawater even with significant pulse distortion caused by dispersion and frequency dependent attenuation. This paper presents the first effort towards the use of machine learning to classify metallic objects in seawater based on EMI sensing.

Development of Precision Controllable Magnetic Field-Assisted Platform for Micro Electrical Machining.

In order to introduce the magnetic field into micro electrical machining technology to explore the influence of magnetic field on micro electrical machining, the development of a precision controllable magnetic field-assisted platform is particularly important. This platform needs to precisely control the spatial magnetic field. This study first completes the hardware design and construction of the magnetic field generation device, using electromagnetic coils with soft iron cores as the sources of the magnetic field. Mathematical models of the magnetic field are established and calibrated. Since the magnetic dipole model cannot effectively describe the magnetic field generated by the electromagnetic coil, this study adopts a more precise description method: the spherical harmonic function expansion model and the magnetic multipole superposition model. The calibration of the magnetic field model is based on actual excitation magnetic field data, so a magnetic field sampling device is designed to obtain the excitation magnetic field of the workspace. The model is calibrated based on a combination of the theoretical model and magnetic field data, and the performance of the constructed setup is analyzed. Finally, a magnetic field-assisted platform has been developed which can generate magnetic fields in any direction within the workspace with intensities ranging from 0 to 0.2 T. Its magnetic field model arrives at an error percentage of 2.986%, a variance of 0.9977, and a root mean square error (RMSE) of 0.71 mT, achieving precise control of the magnetic field in the workspace.

Dipole cosmology in [formula omitted]-gravity

Symmetric teleparallel f(Q)-gravity allows for the presence of a perfect fluid with a tilted velocity in the Kantowski–Sachs geometry. In this dipole model, we consider an ideal gas and we investigate the evolution of the physical parameters. The tilt parameter is constrained by the nonlinear function f(Q) through the non-diagonal equations of the field equations. We find that the dynamics always reduce to the vacuum solutions of STEGR. This includes the Kasner universe, when no cosmological term is introduced by the f(Q) function, and the isotropic de Sitter universe, where fQ plays the role of the cosmological constant. In the extreme tilt limit, the universe is consistently anisotropic and accelerated. However, the final solution matches that of STEGR.

Physics-based discrete models for magneto-mechanical metamaterials

Magneto-mechanical metamaterials are emerging smart materials whose mechanical responses can be tailored through structure architecture and magnetic interactions. The latter provides additional freedom in the material design space and leads to novel behaviors due to its nonlocal nature. The enriched functionalities open new possibilities in various applications, such as actuators, energy absorbers, and soft robots. However, the nonlinear and nonlocal coupling between elastic and magnetic forces poses a great challenge in the modeling and simulation of these systems, further hindering theory-based rational design strategies. Here, we focus on a class of magneto-mechanical metamaterials comprising elastic solids embedded with rigid permanent magnets. The clear separation between elastic and magnetic forces simplifies the design and fabrication process, yet their nonlocal interplay still allows for complex behaviors. We present a simulation framework for such magneto-mechanical metamaterials by combining a lattice spring model for the elastic solid with the dipole model for the magnetic interactions and implementing it in the LAMMPS molecular dynamics software. We demonstrate the capabilities of our framework by simulating a few representative structures, including shape-locking lattice metamaterials, a soft cellular solid with controllable buckling, and a metamaterial chain with phase-transforming behavior. For the shape-locking lattice metamaterials, we successfully capture the magnetic-actuation-driven reconfiguration and the nonlinear mechanical response of the curved lattices. For the soft cellular solid, we identify its buckling patterns under external non-uniform magnetic fields and simulate a buckling evolution process consistent with experiments. For the metamaterial chain, we include the strong long-range interactions among the embedded magnets and reproduce the controllable phase transitions in the experiments. Our work provides a simple yet versatile simulation methodology to investigate the nonlinear mechanical behaviors in the presence of strong external and internal magnetic forces, which will facilitate the design and analysis of magneto-mechanical materials. It can also be applied to other magnetically-driven smart structures, such as soft robots.

Suppression of diffraction in deep-inelastic scattering on nuclei and dynamical mechanism of leading twist nuclear shadowing

Using the leading twist approach (LTA) to nuclear shadowing, we calculate the ratios of diffractive and usual parton distributions for a heavy nucleus (Pb) and the proton, RA/p=fi/AD3/fi/A/fi/pD3/fi/p\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {R}_{A/p}=\\left({f}_{i/A}^{D(3)}/{f}_{i/A}\\right)/\\left({f}_{i/p}^{D(3)}/{f}_{i/p}\\right) $$\\end{document}, for coherent and summed (coherent plus quasi-elastic) nuclear deep-inelastic scattering. We find that RA/p ≈ 0.5 − 1 for quarks as well as for the ratio of the diffractive and total cross sections dσdiff/dMX2/σtoteA/dσdiff/dMX2/σtotep\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {\\left[\\left({d\\sigma}_{\ extrm{diff}}/{d M}_X^2\\right)/{\\sigma}_{\ extrm{tot}}\\right]}_{eA}/{\\left[\\left({d\\sigma}_{\ extrm{diff}}/{d M}_X^2\\right)/{\\sigma}_{\ extrm{tot}}\\right]}_{ep} $$\\end{document} and RA/p ≈ 0.5 − 1.3 for gluons in a broad range of x, including the kinematics of the Electron-Ion Collider, which reaffirms the difference from the nuclear enhancement of RA/p predicted in the gluon saturation framework. We demonstrate that the magnitude of RA/p is controlled by the cross section of the interaction of hadronic fluctuations of the virtual photon with target nucleons, which explains an enhancement of RA/p in the color dipole model and its suppression in LTA. We argue that the black disk limit corresponds to RA/p = 1 and RA/pcoh\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {R}_{A/p}^{\ extrm{coh}} $$\\end{document} = 0.86 for the summed and coherent scattering, respectively. Relying on an intuitive definition of the saturation scale, we show that the ratio of the saturation scales of a heavy nucleus and proton QsA2b/Qsp2b≈1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {Q}_{sA}^2(b)/{Q}_{sp}^2(b)\\approx 1 $$\\end{document} at small impact parameters b due to the strong leading twist nuclear shadowing and diluteness of the nuclear density.

Helmholtz energy models for dipole interactions: Review and comprehensive assessment

Dipolar interactions play an important role for thermodynamic properties of many fluids and accordingly for their modeling. In molecular-based equation of state models, the effect of dipolar interactions is usually described by Helmholtz energy models. There are several Helmholtz energy models for dipolar interactions available in the literature today. In this work, eight dipole contribution models describing the dipole–dipole interactions of fluids were critically assessed by comparing their results with molecular simulation reference data of Stockmayer fluids. Therefore, the dipole contribution models were combined with an accurate Lennard-Jones (LJ) Helmholtz energy model. The following thermodynamic properties were considered in the comparison: vapor pressure, saturated densities, enthalpy of vaporization, surface tension (by using density gradient theory), critical point, second virial coefficient, and thermodynamic properties at homogeneous state points, such as the Helmholtz energy, pressure, chemical potential, internal energy, isochoric heat capacity, isobaric heat capacity, thermal expansion coefficient, isothermal compressibility, thermal pressure coefficient, speed of sound, Joule–Thomson coefficient, and Grüneisen parameter. For the evaluation of the dipole contribution models, molecular simulations for the Stockmayer fluid with the dipole moments of μ2/4πϵ0ɛσ3=0.5,1,2,3,4,5 were carried out. The results indicate, that all considered dipole models exhibit some significant weaknesses. Nevertheless, some dipole contribution models are found to provide a robust description for many properties and state ranges. Overall, the deviations of the dipole contribution models from the Stockmayer simulation data are, in most cases, an order of magnitude higher than the deviations of the LJ EOS from LJ simulation data.

Deep neural network‐based infinitesimal dipole modeling using either near or far electric‐field

AbstractThis paper presents the deep neural network‐based infinitesimal dipole model using either near‐ or far‐field radiation patterns. Based on the radiating characteristic of an infinitesimal dipole, we generated a data set including near and far field radiation patterns corresponding to the phases of infinitesimal dipoles. We used the data set to train and validate the deep neural network (DNN) model. After checking the statistic of the fit function and the average error in expecting the phases of the infinite dipoles, we conclude that the proposed infinitesimal dipole modeling using DNN is sufficient to predict the characteristics of electromagnetic radiation.

Investigation of super-resolution in microsphere-assisted microscopy with the Poynting vector of the dipole model.

In this paper, the Fourier spectrum of an image in microsphere-assisted microscopy (MAM) and the wavenumber decomposition of the Poynting vector of the dipole model are compared for the first time to study the super-resolution performance within several wavelengths in MAM. Firstly, an experiment using microsphere-assisted microscopy is performed, and the fast Fourier transformation (FFT) spectra of the images along the distance are studied. Then the Poynting vector in the point dipole field is theoretically investigated based on the spectral decomposition of dyadic Green's function. Our study finds that the result of decomposition of the Poynting vector corresponds with the propagation results of components with different transverse wavenumbers kρ in an experiment. Even when kρ reaches 1.7k0, the waves can still arrive outside one wavelength. Our work is the first effort (to our knowledge) to associate the Fourier spectrum and the decomposition of the Poynting vector together, and it may contribute to the quantitative exploration of super-resolution performance in MAM in the future.

Enhancing a Many-Body Dipolar Rydberg Tweezer Array with Arbitrary Local Controls.

We implement and characterize a protocol that enables arbitrary local controls in a dipolar atom array, where the degree of freedom is encoded in a pair of Rydberg states. Our approach relies on a combination of local addressing beams and global microwave fields. Using this method, we directly prepare two different types of three-atom entangled states, including a W state and a state exhibiting finite chirality. We verify the nature of the underlying entanglement by performing quantum state tomography. Finally, leveraging our ability to measure multibasis, multibody observables, we explore the adiabatic preparation of low-energy states in a frustrated geometry consisting of a pair of triangular plaquettes. By using local addressing to tune the symmetry of the initial state, we demonstrate the ability to prepare correlated states distinguished only by correlations of their chirality (a fundamentally six-body observable). Our protocol is generic, allowing for rotations on arbitrary sub-groups of atoms within the array at arbitrary times during the experiment; this extends the scope of capabilities for quantum simulations of the dipolar XY model.

Structural Design and Parameter Optimization of Magnetic Gradient Tensor Measurement System.

Magnetic anomaly detection (MAD) technology based on the magnetic gradient tensor (MGT) has broad application prospects in fields such as unexploded ordnance detection and mineral exploration. The difference approximation method currently employed in the MGT measurement system introduces measurement errors. Designing reasonable geometric structures and configuring optimal structural parameters can effectively reduce measurement errors. Based on research into differential MGT measurement, this paper proposes three simplified planar MGT measurement structures and provides the differential measurement matrix. The factors that affect the design of the baseline distance of the MGT measurement system are also theoretically analyzed. Then, using the magnetic dipole model, the error analysis of the MGT measurement structures is carried out. The results demonstrate that the planar cross-shaped structure is optimal, with the smallest measurement error, only 3.15 × 10-10 T/m. Furthermore, employing the control variable method, the impact of sensor resolution constraints, noise level, target magnetic moment, and detection distance on the design of the optimal baseline distance of the MGT measurement system is simulated and verified. The results indicate that the smaller the target magnetic moment, the farther the detection distance, the lower the magnetometer resolution, the greater the noise, and the greater the baseline distance required. These conclusions provide reference and guidance for the construction of the MGT measurement system based on triaxial magnetometers.

Programmable order by disorder effect and underlying phases through dipolar quantum simulators

In this work, we study two different quantum simulators composed of molecules with dipole-dipole interaction through various theoretical and numerical tools. Our first result provides knowledge of the quantum order by disorder effect of the S=1/2 system, which is programmable in a quantum simulator composed of circular Rydberg atoms in the triangular optical lattice with a controllable diagonal anisotropy. When the numbers of up spins and down spins are equal, a set of subextensive degenerate ground states is present in the classical limit, composed of continuous strings whose configuration enjoys a large degree of freedom. Among all possible configurations, we focus on the stripe (up and down spins aligning straightly) and kinked (up and down spins forming zigzag spin chains) patterns. Adopting the the real space perturbation theory, we estimate the leading order energy correction when the nearest-neighbor spin exchange coupling, J, is considered, and the overall model becomes an effective XXZ model with a spatial anisotropy. Our calculation demonstrates a lifting of the degeneracy, favoring the stripe configuration. When J becomes larger, we adopt the infinite projected entangled-pair state (iPEPS) and numerically check the effect of degeneracy lifting. The iPEPS results show that even when the spin exchange coupling is strong the stripe pattern is still favored. Next, we study the dipolar bosonic model with tilted polar angle which can be realized through a quantum simulator composed of cold atomic gas with dipole-dipole interaction in an optical lattice. By placing the atoms in a triangular lattice and tilting the polar angle, the diagonal anisotropy can also be realized in the bosonic system. With our cluster mean-field theory calculation, we provide various phase diagrams with different tilted angles, showing the abundant underlying phases including the supersolid. Our proposal indicates realizable scenarios through quantum simulators in studying the quantum effect as well as extraordinary phases. We believe that our results indicated here can also become a good benchmark for two-dimensional quantum simulators. Published by the American Physical Society 2024