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Second order Heisenberg Uncertainty Principle for solenoidal fields: sharp constants, optimizers and sharp stability

Abstract

The second order Heisenberg Uncertainty Principle of Cazacu, Flynn and Lam is the uncertainty principle for the gradient of a function. Motivated by the question of Maz'ya on the uncertainty principle for divergence-free vector fields, solved by Cazacu, Flynn and Lam for N=2 and by Hamamoto for N≥3, we study the second order principle for divergence-free fields U on ℝN. We prove that ∫|ΔU|2dx∫|x|2|∇U|2dx≥ CN2(∫|∇U|2dx)2, where CN=1+1/2√(N2+8) for N≥3 and C2=1+√2. For the velocity of an incompressible flow, ∫|∇U|2 and ∫|ΔU|2 are, up to constant factors, the enstrophy and the palinstrophy, so the inequality bounds the palinstrophy from below in terms of the enstrophy and the spatial spread of the velocity gradient. The constant CN is sharp and larger than the constant (N+2)/2 for general fields, and all the optimizers are explicit fields with Kummer function profiles. We also obtain the sharp constants on the poloidal and the toroidal fields of each degree. Then we prove the sharp stability of the inequality. In sum form, the deficit controls a chain of squared distances to explicit families of poloidal and toroidal fields, with all the constants sharp. In product form, we find the sharp stability constant in all dimensions. For N≥4 it is 1/2(√(N2+4N−4)−√(N2+8)), and it is attained by swirling flows, the toroidal fields of degree one. On the Fourier side, the sixth order poloidal problem becomes a first order Caffarelli-Kohn-Nirenberg inequality for radial functions, and its stability follows from weighted Poincaré inequalities with Gaussian type measures.

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BibTeX
@misc{do2026second,
  title = {{Second order Heisenberg Uncertainty Principle for solenoidal fields: sharp constants, optimizers and sharp stability}},
  author = {Anh Xuan Do and Anh Tuan Duong and Nguyen Lam and Guozhen Lu and Van Hoang Nguyen},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.00362},
  eprint = {2611.00362},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.00362},
}
RIS
TY  - UNPB
TI  - Second order Heisenberg Uncertainty Principle for solenoidal fields: sharp constants, optimizers and sharp stability
AU  - Anh Xuan Do
AU  - Anh Tuan Duong
AU  - Nguyen Lam
AU  - Guozhen Lu
AU  - Van Hoang Nguyen
PY  - 2026
DA  - 2026/11/01
PB  - arXiv
DO  - 10.48550/arxiv.2611.00362
UR  - https://arxiv.org/abs/2611.00362
AB  - The second order Heisenberg Uncertainty Principle of Cazacu, Flynn and Lam is the uncertainty principle for the gradient of a function. Motivated by the question of Maz'ya on the uncertainty principle for divergence-free vector fields, solved by Cazacu, Flynn and Lam for N=2 and by Hamamoto for N≥3, we study the second order principle for divergence-free fields U on ℝ^N. We prove that ∫|ΔU|^2dx∫|x|^2|∇U|^2dx≥ C_N^2(∫|∇U|^2dx)^2, where C_N=1+1/2√(N^2+8) for N≥3 and C_2=1+√2. For the velocity of an incompressible flow, ∫|∇U|^2 and ∫|ΔU|^2 are, up to constant factors, the enstrophy and the palinstrophy, so the inequality bounds the palinstrophy from below in terms of the enstrophy and the spatial spread of the velocity gradient. The constant C_N is sharp and larger than the constant (N+2)/2 for general fields, and all the optimizers are explicit fields with Kummer function profiles. We also obtain the sharp constants on the poloidal and the toroidal fields of each degree. Then we prove the sharp stability of the inequality. In sum form, the deficit controls a chain of squared distances to explicit families of poloidal and toroidal fields, with all the constants sharp. In product form, we find the sharp stability constant in all dimensions. For N≥4 it is 1/2(√(N^2+4N−4)−√(N^2+8)), and it is attained by swirling flows, the toroidal fields of degree one. On the Fourier side, the sixth order poloidal problem becomes a first order Caffarelli-Kohn-Nirenberg inequality for radial functions, and its stability follows from weighted Poincaré inequalities with Gaussian type measures.
ER  -