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1. Convergence of the Birkhoff normal form sometimes implies convergence of a normalizing transformation

   https://doi.org/10.1017/etds.2021.71  

   DE LA LLAVE, RAFAEL; SAPRYKINA, MARIA (March 2022, Ergodic Theory and Dynamical Systems)

   Abstract Consider an analytic Hamiltonian system near its analytic invariant torus $$\mathcal T_0$$ carrying zero frequency. We assume that the Birkhoff normal form of the Hamiltonian at $$\mathcal T_0$$ is convergent and has a particular form: it is an analytic function of its non-degenerate quadratic part. We prove that in this case there is an analytic canonical transformation—not just a formal power series—bringing the Hamiltonian into its Birkhoff normal form. 

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2. Fast Regression for Structured Inputs

   Meyer, Raphael; Musco, Cameron; Musco, Christopher; Woodruff, David P.; Zhou, Samson (April 2022, International Conference on Learning Representations (ICLR))

   We study the $$\ell_p$$ regression problem, which requires finding $$\mathbf{x}\in\mathbb R^{d}$$ that minimizes $$\|\mathbf{A}\mathbf{x}-\mathbf{b}\|_p$$ for a matrix $$\mathbf{A}\in\mathbb R^{n \times d}$$ and response vector $$\mathbf{b}\in\mathbb R^{n}$$. There has been recent interest in developing subsampling methods for this problem that can outperform standard techniques when $$n$$ is very large. However, all known subsampling approaches have run time that depends exponentially on $$p$$, typically, $$d^{\mathcal{O}(p)}$$, which can be prohibitively expensive. We improve on this work by showing that for a large class of common \emph{structured matrices}, such as combinations of low-rank matrices, sparse matrices, and Vandermonde matrices, there are subsampling based methods for $$\ell_p$$ regression that depend polynomially on $$p$$. For example, we give an algorithm for $$\ell_p$$ regression on Vandermonde matrices that runs in time $$\mathcal{O}(n\log^3 n+(dp^2)^{0.5+\omega}\cdot\text{polylog}\,n)$$, where $$\omega$$ is the exponent of matrix multiplication. The polynomial dependence on $$p$$ crucially allows our algorithms to extend naturally to efficient algorithms for $$\ell_\infty$$ regression, via approximation of $$\ell_\infty$$ by $$\ell_{\mathcal{O}(\log n)}$$. Of practical interest, we also develop a new subsampling algorithm for $$\ell_p$$ regression for arbitrary matrices, which is simpler than previous approaches for $$p \ge 4$$. 

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3. Degenerate linear parabolic equations in divergence form on the upper half space

   https://doi.org/10.1090/tran/8892  

   Dong, Hongjie; Phan, Tuoc; Tran, Hung (June 2023, Transactions of the American Mathematical Society)

   We study a class of second-order degenerate linear parabolic equations in divergence form in ( − ∞ , T ) × R + d (-\infty , T) \times {\mathbb {R}}^d_+ with homogeneous Dirichlet boundary condition on ( − ∞ , T ) × ∂ R + d (-\infty , T) \times \partial {\mathbb {R}}^d_+ , where R + d = { x ∈ R d : x d > 0 } {\mathbb {R}}^d_+ = \{x \in {\mathbb {R}}^d: x_d>0\} and T ∈ ( − ∞ , ∞ ] T\in {(-\infty , \infty ]} is given. The coefficient matrices of the equations are the product of μ ( x d ) \mu (x_d) and bounded uniformly elliptic matrices, where μ ( x d ) \mu (x_d) behaves like x d α x_d^\alpha for some given α ∈ ( 0 , 2 ) \alpha \in (0,2) , which are degenerate on the boundary { x d = 0 } \{x_d=0\} of the domain. Our main motivation comes from the analysis of degenerate viscous Hamilton-Jacobi equations. Under a partially VMO assumption on the coefficients, we obtain the well-posedness and regularity of solutions in weighted Sobolev spaces. Our results can be readily extended to systems. 

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4. The anisotropic Bernstein problem

   https://doi.org/10.1007/s00222-023-01222-4  

   Mooney, Connor; Yang, Yang (January 2024, Inventiones mathematicae)

   Abstract We construct nonlinear entire anisotropic minimal graphs over$$\mathbb{R}^{4}$$ $R^4$, completing the solution to the anisotropic Bernstein problem. The examples we construct have a variety of growth rates, and our approach both generalizes to higher dimensions and recovers and elucidates known examples of nonlinear entire minimal graphs over$$\mathbb{R}^{n},\, n \geq 8$$ $R^n,n\ge 8$. 

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5. Quantitative Rigidity of Differential Inclusions in Two Dimensions

   https://doi.org/10.1093/imrn/rnad108  

   Lamy, Xavier; Lorent, Andrew; Peng, Guanying (May 2023, International Mathematics Research Notices)

   Abstract For any compact connected one-dimensional submanifold $$K\subset \mathbb R^{2\times 2}$$ without boundary that has no rank-one connection and is elliptic, we prove the quantitative rigidity estimate $$\begin{align*} \inf_{M\in K}\int_{B_{1/2}}| Du -M |^2\, \textrm{d}x \leq C \int_{B_1} \operatorname{dist}^2(Du, K)\, \textrm{d}x, \qquad\forall u\in H^1(B_1;\mathbb R^2). \end{align*}$$This is an optimal generalization, for compact connected submanifolds of $$\mathbb R^{2\times 2}$$ without boundary, of the celebrated quantitative rigidity estimate of Friesecke, James, and Müller for the approximate differential inclusion into $SO(n)$. The proof relies on the special properties of elliptic subsets $$K\subset{{\mathbb{R}}}^{2\times 2}$$ with respect to conformal–anticonformal decomposition, which provide a quasilinear elliptic partial differential equation satisfied by solutions of the exact differential inclusion $$Du\in K$$. We also give an example showing that no analogous result can hold true in $$\mathbb R^{n\times n}$$ for $$n\geq 3$$. 

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