3. Research Objectives
The primary goal of this study is to gain a deep understanding of the mechanisms governing quantum and thermal fluctuations of solitons in anisotropic magnets and to evaluate their impact on the magnetic and transport properties of materials. This understanding will enable the development of methods for controlling and manipulating soliton states for use in novel technological applications.
Achieving the stated objectives will contribute significantly to the advancement of materials science and condensed matter physics, expanding the range of practical uses for magnetic solitons in technology and engineering.
This work investigates the dynamic properties of several specific quasi-one-dimensional systems, as examined in references
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| [2] | Mikeska, H.-J., Kolezhuk, A. K. One-dimensional magnetism. In: Schollwöck, U., Richter, J., Farnell, D. J. J., Bishop, R. F. (eds.). Quantum Magnetism. Lecture Notes in Physics, vol. 645. Berlin, Heidelberg: Springer, 2004, pp. 1–83. |
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| [5] | Balents, L. Spin liquids in frustrated magnets. Nature, 2010, 464, 199–208. |
| [6] | Ivanov, B. A., Kolesnichenko, Yu. A. Magnon solitons in anisotropic ferromagnets. JETP, 1999. |
| [7] | Brockmann, M., et al. Quantum and thermal fluctuations in soliton dynamics in quasi-one-dimensional spin systems. Physical Review B, 2013, 87. |
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[1-9]
. These systems prove to be particularly interesting, with several subtle features of their dynamic behavior (such as the central peak, peculiarities of transport processes, etc.) potentially determined by the solitons' response to external perturbations. These effects manifest in the specific behavior of scattering intensity
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| [11] | Abdulloev, Kh. O., Muminov, Kh. Kh., Maksudov, A. On a system of equations in the theory of spin waves. Reports of the Academy of Sciences of the Tajik SSR, 1991, 34(8), 64–68. |
| [12] | Abdulloev, Kh. O., Muminov, Kh. Kh., Maksudov, A. On the correspondence of quantum and classical models in the theory of condensed matter. In: Proceedings of the All-Union Seminar “Interparticle Interactions in Solutions”, 1990, pp. 51–58. |
| [13] | Abdulloev, Kh. O., Rakhimi, F. Exact one-soliton solutions of the dynamic equations of motion of a uniaxial Heisenberg ferromagnet in the SU(3)/SU(2) × U(1) space. Reports of the Academy of Sciences of the Republic of Tajikistan, 40(3–4), 77–80. |
[10-13]
. At high energy transfers, excited soliton states may arise. All of these questions can be explored through the analysis of the double differential scattering cross-section s(q,ω). Thus, a procedure for calculating the dynamic structure factor s(q,ω) is required
| [20] | Scheie, A., Sherman, N. E., Dupont, M., et al. Detection of Kardar–Parisi–Zhang hydrodynamics in a quantum Heisenberg spin-1/2 chain. Nature Physics, 2021, 17(6), 726–730.
https://doi.org/10.1038/s41567-021-01191-6 |
[20]
.
This problem will be the main focus of the present work. The study will employ the approach proposed by Kawasaki
| [14] | Kawasaki, K. Time correlation function of the Sine-Gordon system. Progress of Theoretical Physics, 1976, 55(6), 2029–2030. |
| [22] | Doyon, B., Gopalakrishnan, S., Møller, F., Schmiedmayer, J., Vasseur, R. Generalized hydrodynamics: A perspective. Physical Review X, 2025, 15(1), 010501.
https://doi.org/10.1103/PhysRevX.15.010501 |
[14, 22]
, which was first applied to the problem of neutron scattering by Mikeska
| [15] | Mikeska, H.-J. Solitons in a one-dimensional magnet with an easy plane. Journal of Physics C: Solid State Physics, 1978, 11, L29–L32. |
[15]
, and later developed in and subsequent works
| [16] | Kjems, J. K., Steiner, M. Evidence for soliton modes in the one-dimensional ferromagnet CsNiF3_33. Physical Review Letters, 1978, 41(16), 1137–1140. |
| [17] | Steiner, M., Kakurai, K., Knop, W., Kjems, J. K. Neutron inelastic scattering study of transverse spin fluctuations in CsNiF3_33: A soliton-only central peak. Solid State Communications, 1982, 41(4), 329–332. |
| [18] | Fedyanin, V. K., Makhankov, V. G. Physica Scripta, 1983, 28, 221–228. |
[16-18]
. However, here we will implement it using a simpler method, resulting in a general and straightforward formula and avoiding cumbersome intermediate derivations. This will be illustrated below using several model examples.
Let us discuss the dynamics of one-dimensional Heisenberg ferromagnets with "easy-axis" type anisotropy, whose properties are modeled by the following equation.
(1) a unit vector along the axis, J is the exchange integral (J > 0), A is the anisotropy constant (A > 0). We do not take into account the interaction with lattice vibrations. In this sense, the particle-like excitations described by the soliton solutions of equation (
1) are “purely magnetic” solitons. Let us calculate their contribution to the dynamic structure factor of the ferromagnet.
By choosing the anisotropy axis as the OZ axis, the single-soliton solution of equation (
1) can be written in the form:
(2) Here, the integrals of motion p and r are interpreted as the number of magnons bound in the soliton wave (p>1p > 1p>1) and the quasi-momentum of this wave, respectively
(3) a0 is the lattice constant, p0p_0p0 is the limiting momentum (−p0≤p≤p0-p_0 \leq p \leq p_0−p0 ≤p≤p0). The energy of the wave (1) is given by the formula:
(4) There is a nonlinear relationship between EEE and PPP.
The system described by the Hamiltonian (
1) is fully integrable, and the separation into "kinetic" and "potential" energy is possible in action-angle variables.
For small P (P≪P0):
and mmm can be interpreted as the mass of a bound state of n magnons with mass m.
It should be noted that by analyzing the behavior of equation (
2), one can conclude that for n≫n0, Δ≪Δ0, and for n≤n0, Δ≈Δ0, where Δ0\Delta_0Δ0 is the "true" width of the magnetic soliton.
In this case:
(6) We then have, taking into account the relation (
5):
(7) In this case, Z is calculated exactly; indeed,
(8) and, since
we have the following expression for Z1:
(9) Combining equations (
7) and (
9), and after some transformations, we obtain the following expression for S
1(q,ω):
(10)
(11) and for S(q,ω):
(12) Here, S(q,ω) is given in the zeroth approximation
| [19] | Boothroyd, A. T. Principles of Neutron Scattering from Condensed Matter. Oxford: Oxford University Press, 2020.
https://doi.org/10.1093/oso/9780198862314.001.0001 |
| [22] | Doyon, B., Gopalakrishnan, S., Møller, F., Schmiedmayer, J., Vasseur, R. Generalized hydrodynamics: A perspective. Physical Review X, 2025, 15(1), 010501.
https://doi.org/10.1103/PhysRevX.15.010501 |
[19, 22]
. Assuming that β≫1 and a≫1, we arrive at a Gaussian-type intensity for the quasi-elastic component. Since a is given by formula (
11), this implies that n<n0, and for “massive” solitons such an approximation is not valid.
It should be noted that the central peak and features of soliton transport processes may be determined precisely by the solitons' response to external perturbations, and this can be observed in the specific behavior of the scattering intensity
| [20] | Scheie, A., Sherman, N. E., Dupont, M., et al. Detection of Kardar–Parisi–Zhang hydrodynamics in a quantum Heisenberg spin-1/2 chain. Nature Physics, 2021, 17(6), 726–730.
https://doi.org/10.1038/s41567-021-01191-6 |
| [21] | Gopalakrishnan, S., Vasseur, R. Kinetic theory of spin diffusion and superdiffusion in XXZ spin chains. Physical Review Letters, 2019, 122, 127202.
https://doi.org/10.1103/PhysRevLett.122.127202 |
| [22] | Doyon, B., Gopalakrishnan, S., Møller, F., Schmiedmayer, J., Vasseur, R. Generalized hydrodynamics: A perspective. Physical Review X, 2025, 15(1), 010501.
https://doi.org/10.1103/PhysRevX.15.010501 |
[20-22]
. The analysis of the behavior of the double differential scattering cross-section σs(q,ω) and the calculation of the dynamic structure factor s(q,ω), which were obtained in a simplified manner in this work, serve as evidence of this state.
Modeling the dynamic structure factor of an anisotropic Heisenberg magnet requires a comprehensive approach, including the use of theoretical methods and numerical calculations. Let us consider some key aspects and methods used in such modeling.
Various numerical methods are used to calculate the dynamic structure factor:
1) Quantum Monte Carlo simulations (QMC): This method is suitable for temperature-dependent calculations and provides statistically averaged data on spin configurations
.
2) Exact Diagonalization (ED): Applied to small systems, this method allows obtaining exact eigenstates and eigenvalues of the Hamiltonian.
3) Linear Spin Wave Theory (LSWT): Used for approximate calculations of excitation spectra in magnetic systems, especially effective for systems with low anisotropy.
To perform simulations, one can use specialized software and libraries such as ALPS (Algorithms and Libraries for Physics Simulations), which supports QMC and ED, or environments like MATLAB or Python with NumPy and SciPy libraries for mathematical computations.
These methods and approaches allow for an in-depth study and analysis of the behavior of anisotropic magnets, their spin dynamics, and the influence of various parameters on the physical properties of materials.
Figure 1. Dynamic structure factor S(,ω) as a function of the wave vector q and frequency ω for an anisotropic Heisenberg magnet.
To create a plot of the dynamic structure factor S(,ω) for an anisotropic Heisenberg magnet, we can simulate this process using assumptions about the parameters and certain approximations. In our example, we assume standard values for the exchange interaction J and anisotropy Δ, and then generate data representing S(,ω) as a function of and ω.
For simplicity, we will represent a two-dimensional graph, where the x-axis represents variations of the wave vector q is directed in one-dimensional space, and the y-axis represents the frequency ω. The intensity values of S(,ω) will be visualized through color.
To begin, we assume some simplified functional dependencies for S(,ω). For example, let’s suppose the intensity of the peaks in S(,ω) decreases exponentially with increasing ω and reaches a maximum at specific values of q, corresponding to resonance conditions for spin waves.
Now, let us construct a plot that illustrates these dependencies.
The graph in
Figure 1 shows the dynamic structure factor S(
,ω) for an anisotropic Heisenberg magnet. The x-axis represents the wave vector q, and the y-axis represents the frequency ω. The intensity of S(
,ω), displayed through color, shows resonance peaks under specific conditions that simulate the behavior of spin waves in such a magnet.
This example is based on simplified assumptions about the form of S(,ω) and does not reflect actual experimental data, but it provides an idea of how the dependence of the dynamic structure factor on wave vector and frequency may look in an anisotropic magnet.
Now, let us construct a three-dimensional plot of the dynamic structure factor S(,ω).
Figure 2. Three-dimensional plot of the dynamic structure factor S(,ω)S as a function of the wave vector q and frequency ω for an anisotropic Heisenberg magnet. The surface height and color represent the intensity of the structure factor.
The three-dimensional graph in
Figure 2 shows the dynamic structure factor S(
, ω) of an anisotropic Heisenberg magnet. This visualization provides a clearer representation of how the intensity depends on the wave vector q and the frequency ω. The height of the surface corresponds to the intensity S(
,ω), and the color of the surface indicates the level of this intensity, according to the scale on the right.
The 3D view allows for a better assessment of how the intensity is distributed in the (q,ω) space and how it changes in response to variations in these parameters, offering more detailed insight compared to the 2D representation.
Displaying data in a four-dimensional space S(q,ω) with an additional dimension—such as time or temperature—requires visualization methods capable of conveying the fourth dimension through color, transparency, animation, or other techniques. We can represent it as follows:
1) The axes qqq, ω\omegaω, and S(q,ω) as the three standard dimensions.
2) The fourth dimension — for example, temperature or time — will be represented through color or transparency.
The graph in
Figure 3 presents the dependencies of the dynamic structure factor S(q, ω, T) on the wave vector q, frequency ω\omegaω, and temperature T.
1) Each surface corresponds to a specific temperature T, with its color determined by the scale shown on the right.
2) The intensity S(q,ω,T) decreases as temperature increases, which is visible through the reduction in surface height.
This representation helps visualize the impact of temperature on the dynamic structure of the system in the context of an anisotropic Heisenberg magnet.
Figure 3. The dynamic structure factor S(q,ω,T) as a function of the wave vector q, frequency ω, and temperature T, illustrating the influence of temperature on the dynamic properties of the system.
To create a graph of neutron scattering from solitons in the context of an anisotropic Heisenberg magnet, one must consider the interaction of neutrons with magnetic excitations (solitons) in the material.
Solitons in magnetic systems are stable, localized wave structures that propagate without changing shape and can arise from nonlinear and anisotropic interactions.
Neutron scattering can be described using the scattering cross-section, which depends on changes in the magnetic structure of the material. For a Heisenberg magnet with solitons, modifications of the structure factor caused by soliton dynamics will affect the scattered neutrons.
Modeling soliton dynamics:
First, it is necessary to compute how solitons affect the magnetic state of the system. This can be done using numerical methods such as the finite element method or molecular dynamics simulations.
Calculating the dynamic structure factor:
Next, using data on the magnetic configuration with solitons, the dynamic structure factor S(,ω)S(\vec{q}, \omega)S(q,ω) is calculated, describing how spin excitations influence neutron scattering.
Calculating neutron scattering intensity:
The intensity of scattered neutrons at each angle and energy can be expressed through S(,ω)S(\vec{q}, \omega)S(q,ω), taking into account the specific experimental conditions, such as scattering angle and incoming neutron energy.
To demonstrate this, we will construct a graph showing the dependence of neutron scattering intensity on the scattering angle and energy for solitonic states. We will generate an example of such a graph using simplified assumptions about soliton behavior.
The graph in
Figure 4 shows the neutron scattering intensity from solitons in an anisotropic Heisenberg magnet. The x-axis represents the scattering angle in degrees, and the y-axis represents the energy of scattered neutrons in electron volts. The scattering intensity is shown through color, with darker shades indicating higher intensity.
Intense peaks are visible at scattering angles around 45 and 135 degrees, which correspond to characteristic features of solitonic excitations in such a magnet. These results can be used for planning experimental measurements and further analysis of soliton structure properties in magnetic systems.
For a more detailed analysis of neutron scattering from solitons in an anisotropic Heisenberg magnet, several aspects can be explored:
1) Solitons in magnetic systems are stable, localized nonlinear waves that transport energy and information without dispersion across the magnetic lattice
| [24] | Zvyagin, S. Spin dynamics in quantum sine-Gordon spin chains: High-field ESR studies. Applied Magnetic Resonance, 2021, 52, 337–348. https://doi.org/10.1007/s00723-021-01310-9 |
| [25] | Vaidya, S., Curley, S. P. M., Manuel, P., et al. Magnetic properties of a staggered S = 1 chain with an alternating single-ion anisotropy direction. Physical Review B, 2025, 111, 014421. https://doi.org/10.1103/PhysRevB.111.014421 |
[24, 25]
. In Heisenberg magnets with anisotropy, solitons may arise due to topological features or dynamic nonlinearities in the system.
2) Solitons are described by solutions of equations that take into account anisotropic and exchange interactions in the Heisenberg Hamiltonian. These solutions can be obtained using perturbation theory, numerical integration of equations of motion, or quantum mechanical methods.
3) Quantum aspects of solitons in anisotropic Heisenberg magnets can be examined using quantum field theory. Quantum solitons and their interactions with neutrons can be modeled to predict effects of quantum coherence and quantum fluctuations.
4) Theoretical analysis of neutron scattering involves calculating the dynamic structure factor S(,ω), which shows how changes in magnetic configuration (including solitons) influence scattering. Considering the dependence of S(,ω) on the scattering vector and neutron energy allows for a more detailed picture of interactions.
5) Practical methods for measuring neutron scattering include using neutron spectrometers at research reactors or spallation sources. Measurements should be carried out under various conditions to refine the contribution of solitonic states to the overall scattering spectrum.
After collecting experimental data, a comprehensive analysis is required using data processing methods such as Fourier analysis to identify soliton signatures in scattering spectra.
Now, let us consider the possibility of creating a detailed model or simulation that incorporates these aspects.
Figure 4. Map of the neutron scattering intensity distribution from soliton states in an anisotropic Heisenberg magnet in the coordinates “scattering angle – scattered neutron energy.” The intensity is represented by a color scale, where darker regions correspond to higher scattering values.
To show a more detailed graph that includes the effects of neutron scattering from solitons in an anisotropic Heisenberg magnet, we can simulate changes in scattering intensity as a function of neutron energy and scattering angle, and demonstrate the influence of solitonic states.
Assume that solitons affect the magnetic configuration of the system, causing characteristic peaks in scattering intensity at certain energies and angles. These peaks may be associated with resonance phenomena when neutron energy and momentum are matched with quasiparticles (solitons) in the material.
We simulate solitonic excitations by creating data in which scattering intensity increases at specific energy and angle values, modeling the impact of solitons.
For visualization, we use a heatmap to display scattering intensity as a function of angle and energy.
Let us now create a graph that illustrates this dependency.
The graph in
Figure 5 shows the neutron scattering intensity modeled with consideration of the influence of solitons in an anisotropic Heisenberg magnet. The x-axis represents the scattering angle in degrees, and the y-axis represents the neutron energy in electron volts. The scattering intensity, shown through color, displays resonance peaks at specific angles and energies, which correspond to the characteristics of solitonic excitations.
These peaks indicate that effective interaction with magnetic solitons occurs at certain neutron angles and energies, resulting in enhanced scattering. This can be useful for experimentally confirming the existence of solitons and studying their properties in such systems.
Additionally, we will construct this graph in three-dimensional space.
The three-dimensional graph in
Figure 6 shows the neutron scattering intensity from solitons in an anisotropic Heisenberg magnet. The x-axis represents the scattering angle in degrees, the y-axis represents neutron energy in electron volts, and the surface height corresponds to the scattering intensity. The surface color illustrates the level of intensity, with darker shades indicating higher values.
This visualization provides a clear assessment of how scattering intensity is distributed across angles and energies, highlighting zones of resonant interaction with solitons, which appear as pronounced peaks on the graph.
To visualize data in four-dimensional space—when we already have three dimensions (scattering angle, neutron energy, and scattering intensity)—the fourth dimension can be represented through changes in color, transparency, or surface size on the graph. This fourth dimension can, for example, be temperature or time, which influences the dynamics of the process.
Let us assume that the fourth dimension is the system’s temperature, which affects scattering intensity. Temperature will be reflected through color variation of the surface, with higher temperatures shown in warmer colors.
We will now create a demonstration plot using a temperature gradient to modify the surface color that represents neutron scattering intensity.
Figure 5. Map of the neutron scattering intensity distribution obtained with consideration of the influence of solitons in an anisotropic Heisenberg magnet. In the coordinates “scattering angle–neutron energy,” resonance peaks are observed, reflecting the characteristic features of solitonic excitations. The color scale indicates the magnitude of the scattering intensity.
Figure 6. Three-dimensional map of the neutron scattering intensity distribution from soliton states in an anisotropic Heisenberg magnet. In the coordinates “scattering angle–neutron energy,” both the surface height and the color scale characterize the magnitude of the scattering intensity, where darker regions correspond to higher values.
Figure 7. Three-dimensional visualization of the neutron scattering intensity in an anisotropic Heisenberg magnet with the temperature factor taken into account. The surface color scale characterizes the magnitude of the scattering intensity and its variation with temperature, providing a clear representation of the temperature dependence of the process under study.
Figure 8. Animated visualization of the temporal evolution of the temperature profile and its effect on the neutron scattering intensity from soliton states in an anisotropic Heisenberg magnet. Variations in temperature are accompanied by corresponding changes in the color distribution of the graph, providing a clear illustration of the influence of the temperature factor on the dynamic processes in the material.
The three-dimensional graph in
Figure 7 shows neutron scattering intensity with temperature dependence taken into account in an anisotropic Heisenberg magnet. The surface color, representing scattering intensity, changes with temperature, adding a fourth dimension to our visualization.
Axes: The scattering angle and neutron energy are shown on the horizontal axes, while the scattering intensity is represented on the vertical axis.
Colors: Temperature ranges from lower (blue tones) to higher (yellow tones), as indicated by the color scale.
This visualization clearly illustrates how temperature changes can affect neutron scattering processes in the material, showing how intensity varies under different thermal conditions.
To further enhance the visualization and analysis of neutron scattering data with respect to various parameters, we can extend our graph by adding the following elements:
1) Time-based animation: If we assume that scattering dynamics depend on time (e.g., changes in soliton states over time), animation can help observe how scattering patterns evolve.
2) Interactive elements: Enable real-time adjustments to visualization parameters such as viewing angle, temperature range, or energy levels.
3) Multipanel display: Present multiple aspects of the data simultaneously, for instance, separate panels for different angle or temperature ranges.
4) Depth and transparency: Use transparency to represent less significant data, allowing focus on the more important areas of the graph.
The graph in
Figure 8 presents an animation that demonstrates the change in temperature profile over time and its effect on the neutron scattering intensity from solitons in an anisotropic Heisenberg magnet. During the animation, the temperature varies, and accordingly, the colors on the graph change, allowing a visual assessment of how temperature variations influence the processes within the material.
This is a demonstration example in which the animation provides a dynamic representation of the system’s changing parameters.
It can now be concluded that when neutrons scatter from solitons, there is an exchange of momentum and energy between the neutrons and the magnetic structures of the solitons. The specificity of soliton scattering lies in the fact that they leave a distinct "signature" in the dynamic structure factor S(,ω), leading to characteristic features in the spectrum of scattered radiation.
Temperature influences the spin dynamics in the material, altering soliton properties and thereby modifying neutron scattering. As temperature increases, the amplitude of thermal spin fluctuations may rise, which changes the conditions of soliton–neutron interaction.
Dynamic changes in the scattering process can be illustrated with the help of animation, which shows how scattering evolves over time or with varying temperature. This provides deeper insight into the interactions within the system.
Thus, neutron scattering from solitons in an anisotropic Heisenberg magnet is a complex process involving quantum mechanics, statistical physics, and field theory. Studying such systems helps to understand the fundamental aspects of interactions in condensed matter, with solitons—as stable nonlinear wave structures—playing a key role in the dynamics of many magnetic and electronic materials. Investigating their quantum and thermal fluctuations can shed light on fundamental topics such as interactions between magnetic moments, wavefront propagation, and mechanisms of energy dissipation.
The development of neutron scattering methods is also very important, as neutron scattering is a powerful tool for studying the structural and dynamic properties of materials at the atomic level. Advancing new methodologies and improving existing scattering techniques can significantly enhance our ability to explore complex systems such as anisotropic magnets, especially in the context of their internal dynamics and interaction with external fields.
Magnetic materials that exhibit solitonic properties have potential applications in modern technologies, including information storage, spintronics, and quantum computing. Understanding soliton dynamics can aid in the development of new devices with improved functional characteristics.
It should also be noted that studying the thermal fluctuations of solitons is crucial for assessing the stability of magnetic states at different temperatures. This is especially important for applications requiring high stability and reliability under changing thermal conditions, and understanding the relationships between quantum and thermal fluctuations and their impact on the macroscopic properties of materials opens up new scientific and practical perspectives. For example, controlling such fluctuations may allow for the development of materials with tailored properties for specific applications.
In conclusion, the chosen research topic is not only relevant but also highly promising in terms of scientific discoveries and innovative developments in materials science and physics.