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List of nonlinear partial differential equations

Nonlinear partial differential equations (PDEs) are mathematical equations that relate a function of multiple independent variables to its partial derivatives, where the highest-order derivatives appear nonlinearly, often modeling complex phenomena in physics, engineering, and biology that linear PDEs cannot capture.^[1] A list of such equations serves as a reference compilation of prominent examples, highlighting their forms, applications, and analytical challenges, drawn from fields like fluid dynamics, wave propagation, and reaction-diffusion systems.^[2] These equations are fundamental in describing real-world processes where interactions lead to emergent behaviors, such as turbulence or soliton formation, and their study often involves advanced techniques like characteristic methods, numerical simulations, or conservation laws due to the lack of general superposition principles.^[3] Unlike linear PDEs, nonlinear ones can exhibit phenomena like shock waves, blow-up solutions, or traveling waves, making them central to modern applied mathematics.^[2] Notable examples include Burgers' equation (u_t + u u_x = \nu u_{xx}), a simplified model for viscous fluid flow that illustrates shock formation and diffusion; the Korteweg-de Vries (KdV) equation (u_t + u u_x + u_{xxx} = 0), which governs shallow water waves and supports soliton solutions; and Fisher's equation (u_t = u_{xx} + u(1 - u)), used in population genetics to describe reaction-diffusion processes with traveling wavefronts.^[2] Other canonical cases are the nonlinear Schrödinger equation (i \psi_t + \psi_{xx} + |\psi|^2 \psi = 0), modeling optical solitons and Bose-Einstein condensates, and the Navier-Stokes equations for incompressible fluids (\partial_t \mathbf{u} + (\mathbf{u} \cdot \nabla) \mathbf{u} = -\nabla p + \nu \Delta \mathbf{u}, \nabla \cdot \mathbf{u} = 0), which remain unsolved in three dimensions for general smooth solutions.^[3]

Introduction

Definition and Characteristics

A nonlinear partial differential equation (PDE) involves an unknown function and its partial derivatives that appear in a nonlinear fashion, such as through products of the function with its derivatives, powers of the function or derivatives, or composition within other nonlinear functions.^[4] This contrasts with linear PDEs, where the equation takes the form of a linear combination of the function and its derivatives with coefficients depending only on independent variables.^[4] Key characteristics of nonlinear PDEs include the absence of the superposition principle, which holds for linear PDEs and allows linear combinations of solutions to yield new solutions.^[5] Instead, nonlinearity introduces phenomena such as shock waves from intersecting characteristics, stable localized solitons that preserve shape upon interaction, and blow-up solutions where the solution becomes unbounded in finite time.^[6] These features arise because wave speeds or propagation depend on the solution amplitude itself, leading to breakdowns in smooth solutions that do not occur in linear cases like the heat or wave equations.^[6] Nonlinear PDEs are categorized by the location of nonlinearity: semilinear PDEs are linear in highest-order derivatives but include nonlinear source terms in the function; quasilinear PDEs are linear in highest-order derivatives with coefficients depending on the function and lower-order derivatives; and fully nonlinear PDEs feature nonlinearity directly in the highest-order derivatives.^[4] This classification aids in analyzing solvability and stability, assuming prior knowledge of linear PDEs where superposition simplifies solution construction. Early recognition of nonlinear PDEs appeared in 18th- and 19th-century works by Euler and Lagrange on continuum mechanics and variational principles, which generated such equations through Euler-Lagrange formulations.^[7] Modern study accelerated post-1950s with computational advances enabling numerical simulations and the exploration of integrable systems via symmetry methods pioneered by Sophus Lie.^[7]

Importance and Applications

Nonlinear partial differential equations (PDEs) are crucial for modeling complex, real-world phenomena where linear approximations break down, such as turbulence in fluid flows, pattern formation in biological systems, and relativistic effects in gravitational dynamics. These equations capture the intricate interactions that govern natural processes, providing essential insights into systems exhibiting emergent behaviors not predictable by simpler linear models. In physics, they describe wave propagation and shock formations; in biology, they model population dynamics and tissue growth; and in engineering, they inform designs for structural stability under nonlinear stresses.^[8]^[3] Key applications span multiple disciplines. In fluid dynamics, nonlinear PDEs like the Navier-Stokes equations simulate shock waves and turbulent flows critical for aerodynamics and weather prediction. In quantum field theory, they model soliton waves that represent stable particle-like structures in nonlinear media, aiding advancements in optics and condensed matter physics. In biology, reaction-diffusion equations underpin morphogenesis, explaining pattern formation in animal coats and embryonic development through mechanisms like Turing instability. These applications highlight how nonlinear PDEs enable quantitative predictions in scenarios where superposition principles fail.^[9]^[10]^[3] Solving nonlinear PDEs presents significant challenges, primarily due to the absence of general existence and uniqueness theorems that apply universally, unlike their linear counterparts. While linear PDEs often yield explicit solutions via separation of variables or Fourier transforms, nonlinear ones lack such universality, leading to difficulties in proving solution existence, stability, or long-term behavior. Common approaches include perturbation methods for small nonlinearities, numerical simulations using finite element or finite difference schemes for approximate solutions, and specialized techniques like inverse scattering for integrable cases such as the Korteweg-de Vries equation. These methods are indispensable but computationally intensive, often requiring high-performance computing for practical implementation.^[11]^[12]^[3] As of 2025, modern developments have integrated artificial intelligence and machine learning to address these challenges, with physics-informed neural networks (PINNs) emerging as a powerful tool for approximating solutions to nonlinear PDEs from data. PINNs embed PDE constraints directly into neural network training, enabling efficient solving of forward and inverse problems in high dimensions and significant reductions in computational time compared to traditional methods. Additionally, links to data-driven discovery allow for uncovering hidden PDE structures from observational data, enhancing applications in emerging fields like climate modeling—where nonlinear PDEs simulate atmospheric turbulence and ocean currents—and quantum computing simulations, which leverage quantum algorithms to tackle intractable nonlinear dynamics in weather prediction and molecular interactions. These AI advancements, combined with quantum-inspired methods, promise to revolutionize the analysis of nonlinear PDEs in complex systems.^[13]^[14]^[15]

Alphabetical List

A–F

The Allen–Cahn equation models the dynamics of phase separation and domain coarsening in binary alloys and other materials with conserved order parameters. It is a nonlinear reaction-diffusion partial differential equation typically formulated in one spatial dimension plus time (1+1 dimensions) as

u_t = \epsilon^2 u_{xx} + u - u^3,

where u represents the concentration difference between two phases, \epsilon is a small parameter controlling the interface width, and the nonlinear term u - u^3 arises from a double-well potential driving phase transitions. This equation captures the motion of antiphase boundaries through curvature-driven flow and has been pivotal in phase-field modeling for microstructure evolution. The Bateman-Burgers equation extends the classical Burgers equation by incorporating a variable diffusion coefficient, often used in fluid mechanics to study turbulent flows and shock waves with position-dependent viscosity. In 1+1 dimensions, it takes the form

u_t + u u_x = \nu(x) u_{xx},

where \nu(x) is the diffusion term, allowing for more realistic modeling of inhomogeneous media compared to constant-viscosity cases. This variant highlights the interplay between nonlinear advection and diffusion in propagating disturbances. The Benjamin–Bona–Mahony equation provides a regularized long-wave approximation for unidirectional wave propagation in nonlinear dispersive media, such as shallow water or nonlinear lattices, avoiding the ill-posedness of certain hyperbolic systems. Defined in 1+1 dimensions as

u_t + u_x + u u_x - u_{xxt} = 0,

it features a mixed derivative term that introduces dispersion, leading to stable solitary wave solutions. Its applications include tsunami modeling and ion-acoustic waves in plasmas. The Benjamin–Ono equation describes the evolution of internal waves in stratified fluids, particularly in deep water where the dispersion relation involves the Hilbert transform. In 1+1 dimensions, it is expressed as

u_t + H(u_{xx}) + u u_x = 0,

with H denoting the Hilbert transform, which captures nonlocal effects essential for wave stability. This equation is integrable and exhibits soliton interactions relevant to oceanography and atmospheric dynamics. The Born–Infeld equation reformulates classical electrodynamics to impose a finite speed of propagation for electromagnetic signals, addressing singularities in Maxwell's equations. In 1+1 dimensions, it appears as a nonlinear wave equation for the electric field E:

\left(1 - E^2\right)^{3/2} E_{tt} - E_{xx} = 0,

bounding the field strength to prevent infinite energies. Originally proposed for relativistic electron theory, it influences modern studies in nonlinear optics and string theory. The Boussinesq equation approximates the propagation of surface water waves in shallow channels, incorporating both nonlinearity and dispersion for improved accuracy over linear theories. A common 1+1 dimensional form is the "good" Boussinesq equation:

u_{tt} - u_{xx} - u_{xxxx} - 3(u^2)_{xx} = 0,

which supports cnoidal waves and solitons. It is fundamental in coastal engineering and hydraulic modeling. The Bretherton equation governs the stability and dynamics of thin liquid films flowing down inclined surfaces under gravity, capturing the onset of fingering instabilities due to nonlinear surface tension effects. In 1+1 dimensions for film thickness h:

h_t + (h^3 + 3 h^2 \delta h_x)_x = 0,

approximately, where \delta relates to slip length. This model is key in microfluidics and coating processes. Burgers' equation serves as a canonical one-dimensional model for the formation and dissipation of shock waves in compressible fluids, simplifying the Navier-Stokes equations while retaining essential nonlinear and diffusive features. In 1+1 dimensions:

u_t + u u_x = \nu u_{xx},

with \nu > 0 as viscosity; in the inviscid limit (\nu \to 0), it develops discontinuities. It is widely used in turbulence theory and traffic flow simulations. The Cahn–Hilliard equation describes the conserved dynamics of phase separation in binary mixtures, emphasizing mass conservation through a fourth-order structure. In arbitrary spatial dimensions d, it is

u_t = \nabla \cdot (M(u) \nabla \mu), \quad \mu = -\gamma \Delta u + f'(u),

where M(u) is mobility, \gamma interfacial energy, and f(u) the free energy density (e.g., double-well). Applications span alloy solidification and polymer blends. The Camassa–Holm equation models shallow water waves with peaked solitons (peakons) that preserve particle-like properties under collisions, arising from reanalysis of the Green-Naghdi equations. In 1+1 dimensions:

u_t - u_{xxt} + 3u u_x = 2 u_x u_{xx} + u u_{xxx},

or equivalently in nonlocal form involving a Helmholtz operator. It is integrable and applied to tsunamis and nonlinear acoustics. The Chafee–Infante equation, a reaction-diffusion system in bounded domains, illustrates bistable dynamics where stable uniform states compete, often studied in 1+1 dimensions as

u_t = u_{xx} + u(1 - u)(u - a),

with $0 < a < 0.5 for bistability. Though ODE-like in zero spatial dimensions for equilibria, its PDE form analyzes front propagation in combustion and ecology. The Degasperis–Procesi equation generalizes the Camassa–Holm equation for shallow water waves, featuring a higher nonlinearity parameter and also supporting peakons. In 1+1 dimensions:

u_t - u_{xxt} + 4u u_x = 3u_x u_{xx} + u u_{xxx},

it is completely integrable via inverse scattering. Used in modeling breaking waves and orbital stability. The Dym equation is an integrable nonlinear PDE exhibiting soliton solutions through its connection to the Korteweg–de Vries hierarchy via reciprocal transformations. In 1+1 dimensions:

u_t = u^3 u_{xxx},

it preserves positivity and is linked to random matrix theory. Applications include statistical mechanics of eigenvalues. The Eikonal equation arises as the high-frequency limit of wave equations in geometrical optics and as a Hamilton-Jacobi equation in control theory. In arbitrary dimensions:

|\nabla u| = n(\mathbf{x}),

where n(\mathbf{x}) is the refractive index, it determines ray paths via characteristics. Solved by fast marching methods in imaging and seismology. The Einstein field equations form the core of general relativity, coupling spacetime geometry to matter-energy distribution through nonlinear tensor relations. In 3+1 dimensions (or general d+1):

R_{\mu\nu} - \frac{1}{2} R g_{\mu\nu} = \frac{8\pi G}{c^4} T_{\mu\nu},

where R_{\mu\nu} is the Ricci tensor, R the scalar curvature, g_{\mu\nu} the metric, G gravitational constant, c speed of light, and T_{\mu\nu} the stress-energy tensor. They predict black holes, gravitational waves, and cosmology. The inviscid Euler equations describe the motion of ideal fluids without viscosity, balancing nonlinear convection with pressure gradients. In 1+3 dimensions for velocity \mathbf{u} and pressure p:

\partial_t \mathbf{u} + (\mathbf{u} \cdot \nabla) \mathbf{u} = -\nabla p, \quad \nabla \cdot \mathbf{u} = 0,

with incompressibility; they support vortex dynamics and shocks. Central to aerodynamics and astrophysical flows.

G–K

The Ginzburg–Landau equation is a fundamental model in superconductivity and superfluidity, describing the behavior of an order parameter ψ near critical points. In its time-dependent form for one time and three spatial dimensions, it reads:

\partial_t \psi = \nabla^2 \psi + \psi (1 - |\psi|^2)

This equation captures phase transitions and vortex dynamics in type-II superconductors. The Gross–Pitaevskii equation models the dynamics of Bose–Einstein condensates, representing the macroscopic wave function of weakly interacting bosons.^[16] For one time and n spatial dimensions, its standard form is:

i \hbar \partial_t \psi = -\frac{\hbar^2}{2m} \nabla^2 \psi + V \psi + g |\psi|^2 \psi

Here, V denotes an external potential, and g the interaction strength; solutions exhibit solitons and vortices in trapped condensates.^[16] The Hasegawa–Mima equation governs drift wave turbulence in plasmas, particularly ion acoustic and electrostatic modes in magnetized settings. In one time and three spatial dimensions, it takes the form:

\partial_t (\nabla^2 \phi - \phi) + [\phi, \nabla^2 \phi] + V_{0x} \partial_y \phi = 0

where [·,·] denotes the Poisson bracket and V_{0x} a constant shear flow; it predicts zonal flows and anomalous transport in tokamaks. The Hunter–Saxton equation describes the dynamics of liquid crystal directors, focusing on orientation fields in nematic phases. For one time and one spatial dimension, it is given by:

u_t + u u_x = \frac{1}{2} \int_0^x u_x^2 \, ds

This integrable system exhibits wave breaking and singular solutions, relevant to defect formation in aligned molecules. The Kadomtsev–Petviashvili (KP) equation extends the KdV model to two spatial dimensions, analyzing the stability of long waves with weak transverse perturbations.^[17] In one time and two spatial dimensions, the standard form is:

(u_t + 6 u u_x + u_{xxx})_x + 3 \sigma^2 u_{yy} = 0

with σ = ±1 distinguishing KP-I and KP-II hierarchies; it supports line solitons and resonant interactions in water waves and ion-acoustic plasmas.^[17] The Kaup–Kupershmidt equation is an integrable fifth-order KdV-type system, arising in the classification of nonlinear evolution equations with bi-Hamiltonian structure. For one time and one spatial dimension, it reads:

u_t + u_{xxxxx} + 10 u u_{xxx} + 25 u_x u_{xx} + 20 u^2 u_x = 0

This equation admits multi-soliton solutions via inverse scattering and models higher-order dispersive waves. The Korteweg–de Vries (KdV) equation models shallow water solitons and unidirectional wave propagation with dispersion and nonlinearity balancing.^[18] In one time and one spatial dimension, the canonical form is:

u_t + 6 u u_x + u_{xxx} = 0

A modified variant replaces the quadratic nonlinearity:

v_t + 6 v^2 v_x + v_{xxx} = 0

These exhibit exact N-soliton solutions and infinite conservation laws, applicable to ion-acoustic waves and lattice vibrations.^[18] The Kuramoto–Sivashinsky equation captures chaotic pattern formation in combustion fronts and thin film flows, combining instability and stabilizing diffusion. For one time and n spatial dimensions, it is:

u_t + \nabla^2 u + \nabla^4 u + \frac{1}{2} |\nabla u|^2 = 0

Solutions display spatiotemporal chaos and cellular structures, with low-dimensional attractors in bounded domains.

L–Q

The Landau–Lifshitz equation models the precessional and damping dynamics of magnetization in ferromagnetic materials under an effective magnetic field. In its standard form, the equation reads

\partial_t \mathbf{m} = -\gamma \mathbf{m} \times \mathbf{H}_{\mathrm{eff}} + \alpha \mathbf{m} \times \partial_t \mathbf{m},

where \mathbf{m} is the unit magnetization vector, \gamma > 0 is the gyromagnetic ratio, \mathbf{H}_{\mathrm{eff}} incorporates exchange, anisotropy, and external fields, and \alpha \geq 0 is the Gilbert damping coefficient. This 1+3 dimensional PDE, first derived in 1935, captures micromagnetic phenomena such as spin waves and domain wall motion on nanosecond timescales.^[19] The Liouville equation arises in the study of conformal metrics on surfaces with prescribed constant Gaussian curvature. It takes the form

\Delta u = -K e^{2u},

where u is a scalar potential function, \Delta is the Laplace–Beltrami operator, and K is a constant (often normalized to \pm 1). This nonlinear elliptic PDE, dating to 1853, enables explicit parametrization of surfaces like pseudospheres (K < 0) or catenoids, with solutions expressible via logarithms of Jacobi elliptic functions for bounded domains. Its any-dimensional variants appear in complex analysis for prescribing curvatures on Riemann surfaces.^[20] The Monge–Ampère equation is a fully nonlinear elliptic PDE central to convex analysis, Kähler geometry, and optimal transport problems. The canonical form is

\det(D^2 u) = f(x),

where D^2 u is the Hessian matrix of the convex function u: \mathbb{R}^n \to \mathbb{R}, and f > 0 is a given density function. Originating in 1781 for minimal surfaces, modern applications include solving the Monge–Kantorovich mass transport problem, where solutions yield optimal maps between probability measures via \nabla u. Regularity theory ensures C^{1,\alpha} solutions under strict convexity assumptions.^[21] The Navier–Stokes equations describe the motion of viscous, incompressible fluids in three spatial dimensions plus time. The momentum equation is

\partial_t \mathbf{u} + (\mathbf{u} \cdot \nabla) \mathbf{u} = -\nabla p + \nu \nabla^2 \mathbf{u} + \mathbf{f},

coupled with the incompressibility condition \nabla \cdot \mathbf{u} = 0, where \mathbf{u} is the velocity field, p is pressure, \nu > 0 is kinematic viscosity, and \mathbf{f} represents external forces. Formulated in the 1820s–1840s, these equations model phenomena like turbulence and boundary layers, but global existence and smoothness for all smooth initial data in 3D remain unsolved, earning a $1 million Millennium Prize. The cubic nonlinear Schrödinger equation governs envelope solitons in nonlinear wave propagation. In normalized 1+1 dimensions, it is

i \partial_t \psi + \partial_{xx} \psi + 2 |\psi|^2 \psi = 0,

where \psi is a complex amplitude. Derived in 1973 for anomalous dispersion in optical fibers, it predicts self-focusing and bright solitons stable under perturbations. In quantum many-body systems, this form underlies the Gross–Pitaevskii equation for Bose–Einstein condensates at zero temperature, describing superfluid dynamics and vortex formation in dilute gases. The derivative nonlinear Schrödinger equation extends the cubic model with self-steepening terms relevant to femtosecond pulse propagation in birefringent fibers. A key variant is

i q_t + q_{xx} + 2 i |q|^2 q_x + |q|^2 q = 0,

where q is the complex envelope. Introduced in 1979 for plasma physics, it applies in nonlinear optics to circularly polarized waves, yielding chirped solitons and peakons via inverse scattering, with applications to high-intensity laser filamentation.^[22] The porous medium equation models slow diffusion processes where permeability depends on saturation, such as gas flow through soils. In n spatial dimensions plus time, it is

u_t = \Delta (u^m),

with m > 1 yielding degenerate nonlinearity (diffusivity vanishes at u=0). First analyzed mathematically in the 1950s, it exhibits finite-speed propagation and self-similar Barenblatt solutions u \sim t^{-k} (C - \xi^2)_+^{1/(m-1)}, applied to glaciology, combustion fronts, and population dynamics with Allee effects.^[23]

R–Z, α–ω

The Ricci flow is a nonlinear partial differential equation that governs the evolution of a Riemannian metric g_{ij} on a manifold, given by

\partial_t g_{ij} = -2 R_{ij},

where R_{ij} is the Ricci curvature tensor. Introduced by Richard Hamilton in 1982, this equation deforms the metric in a manner analogous to the heat equation, smoothing out irregularities in the geometry while preserving volume when normalized. It has applications in geometric analysis, particularly for studying the topology of manifolds. The Ricci flow played a pivotal role in Grigori Perelman's proof of the Poincaré conjecture in 2002–2003, where surgery techniques were used to handle singularities, demonstrating that every simply connected, closed 3-manifold is homeomorphic to the 3-sphere. The Seiberg–Witten equations form a system of nonlinear partial differential equations in gauge theory, defined on a 4-manifold with a U(1) connection A and a spinor \phi as

D_A \phi = 0, \quad F^+_A = \sigma(\phi),

where D_A is the Dirac operator, F^+_A is the self-dual part of the curvature 2-form, and \sigma(\phi) is a quadratic map from the spinor bundle. Developed by Nathan Seiberg and Edward Witten in 1994, these equations arise from the low-energy effective action of \mathcal{N}=2 supersymmetric Yang–Mills theory and provide invariants for smooth 4-manifolds, simplifying earlier Donaldson invariants. They are elliptic and gauge-invariant, enabling the study of monopole moduli spaces and Donaldson-type theorems with reduced technical complexity. The sine–Gordon equation is a nonlinear wave equation in 1+1 dimensions,

\phi_{tt} - \phi_{xx} + \sin \phi = 0,

exhibiting soliton solutions such as kinks and breathers due to its integrability via inverse scattering transform. First appearing in the Frenkel–Kontorova model for crystal dislocations in 1938–1939, it models topological defects and has applications in particle physics for bosonic solitons and in condensed matter for phenomena like Josephson junctions in superconductors, where the sine term arises from nonlinear periodic potentials. The Swift–Hohenberg equation describes pattern formation in systems near the onset of instability, typically in any spatial dimension but often studied in 1D or 2D,

\partial_t u = r u - (1 + \nabla^2)^2 u - g u^3,

with r as a control parameter for bifurcation and g > 0 for supercriticality. Derived by Jack Swift and Pierre Hohenberg in 1977 to model Rayleigh–Bénard convection, it captures the emergence of striped or hexagonal patterns through linear instability at wavenumber 1, stabilized by higher-order diffusion. This amplitude equation framework highlights universal behaviors in nonequilibrium systems, such as Turing patterns in reaction-diffusion models. The source-free Yang–Mills equations are a system of nonlinear partial differential equations for a connection on a principal bundle in any dimension,

D_\mu F^{\mu\nu} = 0,

where F^{\mu\nu} is the curvature 2-form and D_\mu is the covariant derivative. Formulated by Chen Ning Yang and Robert Mills in 1954 as a non-Abelian generalization of Maxwell's equations, they describe the dynamics of gauge fields in quantum field theory, underlying the strong and electroweak interactions in the Standard Model. Instanton solutions and moduli spaces of these equations reveal topological structures, with applications in Yang–Mills mass gap problems and Donaldson–Uhlenbeck–Yau theorem for stable bundles. The Zakharov system models the interaction of high-frequency Langmuir waves with low-frequency ion acoustic waves in unmagnetized plasma in 1+3 dimensions,

i E_t + \nabla^2 E = n E, \quad n_{tt} - \nabla^2 n = \nabla^2 |E|^2,

where E is the electric field envelope and n the density perturbation. Introduced by Vladimir Zakharov in 1972, it captures wave collapse and self-focusing phenomena, leading to singularities in finite time under certain initial conditions. This coupled system is integrable in 1+1 dimensions but exhibits dispersive turbulence in higher dimensions, with relevance to laser-plasma interactions and inertial confinement fusion. The \phi^4 theory refers to the nonlinear Klein–Gordon equation for a scalar field in 1+1 or higher dimensions,

\square \phi + \frac{\partial V}{\partial \phi} = 0, \quad V(\phi) = \frac{\lambda}{4} (\phi^2 - v^2)^2,

with double-well potential enabling spontaneous symmetry breaking and kink solitons. A cornerstone of quantum field theory since the 1950s, it serves as a prototype for renormalizable interacting theories, modeling Higgs mechanism analogs and phase transitions. In Euclidean formulation, it provides a PDE framework for constructive QFT in 3D, addressing triviality bounds and ultraviolet divergences through stochastic quantization. For completeness, the Broer–Kaup equations extend shallow-water models in 1+1 dimensions to bidirectional long waves,

p_t - q_{xx} + p p_x = 0, \quad q_t + p_x = 0,

preserving Hamiltonian structure and integrable via Hirota method. Developed by Leo Broer and David Kaup in the late 1970s as a higher-order Boussinesq-type system, they describe nonlinear dispersive waves without breaking, applicable to coastal engineering and tsunami propagation. The Dodd–Bullough equation is an integrable model in quantum field theory, featuring exponential nonlinearities in a relativistic scalar field. In 1+1 dimensions, it takes the Klein-Gordon form

u_{tt} - u_{xx} = e^{u} + e^{-2u},

admitting soliton solutions through Bäcklund transformations. Introduced by Roger Dodd and Robin Bullough in 1970 as a variant of the sine-Gordon equation with asymmetric exponential terms, it arises in integrable hierarchies and affine Toda theories, with connections to quantum integrable systems.

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