BPS and Semi-BPS Kink Families in N-Component Scalar Field Theories with Fourth-Degree Polynomial Potentials
DOI:
https://doi.org/10.66972/iscis21202623Keywords:
Topological Solitons, Kink Families, Bogomolny Formalism, Multi-Component Scalar Fields, Poschl-Teller Spectrum, Physics-Informed Neural NetworksAbstract
We develop a constructive theory of kink solutions in N-component scalar field theories in (1+1) dimensions whose self-interactions are at most quartic and which carry a discrete symmetry. Working inside the Bogomolny first-order framework, we build the potentials from superpotentials and classify the models that support continuous families of BPS and semi-BPS kinks. The two-component MSTB and BNRT systems, together with the recently introduced single-singular-point models, reappear as the N=2 slice of a much larger landscape. The central result is a fully explicit one-parameter family of N-component quartic potentials for which we determine the 2N vacua, the first-order semi-BPS equations, the embedded one-component kinks, the exact energy sum rules, and the closed-form transverse Poschl-Teller spectra. The composite defects are interpreted through exact energy budgets. Because the generic profiles are not elementary, we show that a physics-informed neural network integrates the first-order equations directly and comment on multi-field solitons in the life sciences.
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[1] Vilenkin, A., & Shellard, E. P. S. (1994). Cosmic strings and other topological defects. Cambridge University Press.
[2] Manton, N., & Sutcliffe, P. (2004). Topological solitons. Cambridge University Press. https://doi.org/10.1017/CBO9780511617034
[3] Rajaraman, R. (1982). Solitons and instantons: An introduction to solitons and instantons in quantum field theory. North-Holland.
[4] Bazeia, D., dos Santos, M. J., & Ribeiro, R. F. (1995). Solitons in systems of coupled scalar fields. Physics Letters A, 208, 84–88. https://doi.org/10.1016/0375-9601(95)00756-S
[5] Gani, V. A., Kudryavtsev, A. E., & Lizunova, M. A. (2014). Kink interactions in the (1+1)-dimensional ϕ6 model. Physical Review D, 89, 125009. https://doi.org/10.1103/PhysRevD.89.125009
[6] Kevrekidis, P. G., & Cuevas-Maraver, J. (Eds.). (2019). A dynamical perspective on the ϕ4 model: Past, present and future. Springer. https://doi.org/10.1007/978-3-030-11839-6
[7] Vachaspati, T. (2006). Kinks and domain walls: An introduction to classical and quantum solitons. Cambridge University Press. https://doi.org/10.1017/CBO9780511535192
[8] Shnir, Y. M. (2018). Topological and non-topological solitons in scalar field theories. Cambridge University Press. https://doi.org/10.1017/9781108555623
[9] Weinberg, E. J. (2012). Classical solutions in quantum field theory: Solitons and instantons in high energy physics. Cambridge University Press. https://doi.org/10.1017/CBO9781139017787
[10] Coleman, S. (1985). Aspects of symmetry: Selected Erice lectures. Cambridge University Press. https://doi.org/10.1017/CBO9780511565045
[11] Skyrme, T. H. R. (1962). A unified field theory of mesons and baryons. Nuclear Physics, 31, 556–569. https://doi.org/10.1016/0029-5582(62)90775-7
[12] Alonso-Izquierdo, A., Gonzalez Leon, M. A., & Mateos Guilarte, J. (2002). Kink variety in systems of two coupled scalar fields in two space-time dimensions. Physical Review D, 65, 085012. https://doi.org/10.1103/PhysRevD.65.085012
[13] Bazeia, D., Nascimento, J. R. S., Ribeiro, R. F., & Toledo, D. (1997). Soliton stability in systems of two real scalar fields. Journal of Physics A: Mathematical and General, 30, 8157–8166. https://doi.org/10.1088/0305-4470/30/23/015
[14] Montonen, C. (1976). On solitons with an Abelian charge in scalar field theories (I). Nuclear Physics B, 112, 349–357. https://doi.org/10.1016/0550-3213(76)90537-X
[15] Bazeia, D., Losano, L., & Malbouisson, J. M. C. (2002). Deformed defects. Physical Review D, 66, 101701. https://doi.org/10.1103/PhysRevD.66.101701
[16] Bogomolny, E. B. (1976). The stability of classical solutions. Soviet Journal of Nuclear Physics, 24, 449–454.
[17] Alonso-Izquierdo, A., Gonzalez Leon, M. A., & Mateos Guilarte, J. (2000). N = 2 supersymmetric kinks and real algebraic curves. Physics Letters B, 480, 373–380. https://doi.org /10.1016/S0370-2693(00)00406-8
[18] Wess, J., & Zumino, B. (1974). Supergauge transformations in four dimensions. Nuclear Physics B, 70, 39–50. https://doi.org/10.1016/0550-3213(74)90355-1
[19] Shifman, M., & Voloshin, M. B. (1998). Degenerate domain wall solutions in supersymmetric theories. Physical Review D, 57, 2590–2598. https://doi.org/10.1103/PhysRevD.57.2590
[20] Alonso-Izquierdo, A., Gonzalez Le on, M. A., Gonzalez-Parra, A., & Martın-Vaquero, J. (2026). BPS and semi-BPS kink families in two-component scalar field theories with fourth-degree polynomial potentials. Chaos, Solitons & Fractals, 210, 118570. https://doi.org/10.1016/j.chaos.2026.118570
[21] Alonso-Izquierdo, A. (2018). Reflection, transmutation, annihilation, and resonance in two-component kink collisions. Physical Review D, 97, 045016. https://doi.org/10.1103/PhysRevD.97.045016
[22] Lagaris, I. E., Likas, A., & Fotiadis, D. I. (1998). Artificial neural networks for solving ordinary and partial differential equations. IEEE Transactions on Neural Networks, 9(5), 987–1000. https://doi.org/10.1109/72.712178
[23] Raissi, M., Perdikaris, P., & Karniadakis, G. E. (2019). Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Journal of Computational Physics, 378, 686–707. https://doi.org/10.1016/j.jcp.2018.10.045
[24] Karniadakis, G. E., Kevrekidis, I. G., Lu, L., Perdikaris, P., Wang, S., & Yang, L. (2021). Physics-informed machine learning. Nature Reviews Physics, 3, 422–440. https://doi.org/10.1038/s42254-021-00314-5
[25] Lu, L., Meng, X., Mao, Z., & Karniadakis, G. E. (2021). DeepXDE: A deep learning library for solving differential equations. SIAM Review, 63, 208–228. https://doi.org/10.1137/19M1274067
[26] Sirignano, J., & Spiliopoulos, K. (2018). DGM: A deep learning algorithm for solving partial differential equations. Journal of Computational Physics, 375, 1339–1364. https://doi.org/10.1016/j.jcp.2018.08.029
[27] Cuomo, S., Di Cola, V. S., Giampaolo, F., Rozza, G., Raissi, M., & Piccialli, F. (2022). Scientific machine learning through physics-informed neural networks: Where we are and what’s next. Journal of Scientific Computing, 92, 88. https://doi.org/10.1007/s10915-022-01939-z
[28] Davydov, A. S. (1985). Solitons in molecular systems. D. Reidel Publishing Company. https://doi.org/10.1007/978-94-017-3025-9
[29] Heimburg, T., & Jackson, A. D. (2005). On soliton propagation in biomembranes and nerves. Proceedings of the National Academy of Sciences of the United States of America, 102, 9790–9795. https://doi.org/10.1073/pnas.0503823102
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