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Garving K. Luli

Publications and source records attributed to Garving K. Luli.

At least 19 recordsLinked to original sources

Smooth solutions to systems of linear inequalities on $\mathbb{R}$

Fix an integer $m\geq 0$. We study the one-dimensional problem of deciding when a system of linear inequalities \begin{equation*} \sum_{j=1}^M A_{ij}(x)F_j(x)\leq f_i(x),\qquad i=1,\ldots,N, \end{equation*} with fixed semialgebraic coefficients $A_{ij}:\mathbb R\to\mathbb R$ and given functions \begin{equation*} f_i\in C^\infty(\mathbb R),\qquad i=1,\ldots,N, \end{equation*} admits a solution \begin{equation*} F=(F_1,\ldots,F_M)\in C^m(\mathbb R,\mathbb R^M). \end{equation*} The analogous problem for systems of linear equations admits a finite linear differential criterion, whereas for systems of inequalities such a criterion fails in general in dimensions at least two, already for continuous solutions. This paper gives a complete answer in one dimension for a system of linear inequalities. For $m=0,1,2$, the existence of a $C^m$ solution is characterized by a finite differential criterion. In contrast, for every $m\geq 3$, no finite criterion of this local differential type exists in general, even for a fixed constant-coefficient system. Thus, $m=2$ is the sharp regularity threshold for finite differential characterization of the one-dimensional inequality problem.

math.CA

Optimal $C^{1,1}$ and Quasi-Optimal $C^2$ Monotone Interpolation with Curvature Control

We study monotone Hermite interpolation on an interval, where both function values and first derivatives are prescribed at the nodes. Among all $C^{1,1}$ interpolants, we seek one with optimal curvature, measured by $\|F''\|_{L^\infty}$. In this paper, we analyze the limitations of some classical techniques, and provide an explicit optimal construction in $C^{1,1}$ given by quadratic splines by studying the optimal velocity profile. Moreover, given $E = \{x_1,\cdots,x_N\}$ and $f: E\to \mathbb{R}$ (without derivatives), we also provide a formula to compute the corresponding trace seminorm \[ \inf\Bigl\{ \|F''\|_{L^\infty} : F(x)=f(x) \text{ on $E$ and } F'\ge 0 \text{ everywhere} \Bigr\}. \] In addition, we also describe how to mollify $C^{1,1}$ solutions to $C^2$ while preserving monotonicity and sacrificing a controlled amount of optimality.

math.CA

On $C^m$ Solutions to Systems of Linear Inequalities

Recent work of C. Fefferman and the first author has demonstrated that the linear system of equations \begin{equation*} \sum_{j=1}^M A_{ij}(x)F_j(x)=f_i(x)\hspace{.2in} (i=1,...,N), \end{equation*} has a $C^m$ solution $F=(F_1,...,F_M)$ if and only if $f_1,...,f_N$ satisfy a certain finite collection of partial differential equations. Here, the $A_{ij}$ are fixed semialgebraic functions. In this paper, we consider the analogous problem for systems of linear inequalities: \begin{equation*} \sum_{j=1}^M A_{ij}(x)F_j(x)\le f_i(x)\hspace{.2in} (i=1,...,N). \end{equation*} Our main result is a negative one, demonstrated by counterexample: the existence of a $C^m$ solution $F$ may not, in general, be determined via an analogous finite set of partial differential inequalities in $f_1,...,f_N$.

math.CA

Smooth Selection for Infinite Sets

Whitney's extension problem asks the following: Given a compact set $E\subset\mathbb{R}^n$ and a function $f:E\to \mathbb{R}$, how can we tell whether there exists $F\in C^m(\mathbb{R}^n)$ such that $F=f$ on $E$? A 2006 theorem of Charles Fefferman \cite{F06} answers this question in its full generality. In this paper, we establish a version of this theorem adapted for variants of the Whitney extension problem, including nonnegative extensions and the smooth selection problems. Among other things, we generalize the Finiteness Principle for smooth selection by Fefferman-Israel-Luli \cite{FIL16} to the setting of infinite sets. Our main result is stated in terms of the iterated Glaeser refinement of a bundle formed by taking potential Taylor polynomials at each point of $E$. In particular, we show that such bundles (and any bundles with closed, convex fibers) stabilize after a bounded number of Glaeser refinements, thus strengthening the previous results of Glaeser, Bierstone-Milman-Pawłucki, and Fefferman which only hold for bundles with affine fibers.

math.FA

$C^2$ Interpolation with Range Restriction

Given $ -\infty< λ< Λ< \infty $, $ E \subset \mathbb{R}^n $ finite, and $ f : E \to [λ,Λ] $, how can we extend $ f $ to a $ C^m(\mathbb{R}^n) $ function $ F $ such that $ λ\leq F \leq Λ$ and $ ||F||_{C^m(\mathbb{R}^n)} $ is within a constant multiple of the least possible, with the constant depending only on $ m $ and $ n $? In this paper, we provide the solution to the problem for the case $ m = 2 $. Specifically, we construct a (parameter-dependent, nonlinear) $ C^2(\mathbb{R}^n) $ extension operator that preserves the range $[λ,Λ]$, and we provide an efficient algorithm to compute such an extension using $ O(N\log N) $ operations, where $ N = #(E) $.

math.CA

Algorithms for Nonnegative $C^2(\mathbb{R}^2)$ Interpolation

Let $ E \subset \mathbb{R}^2 $ be a finite set, and let $ f : E \to [0,\infty) $. In this paper, we address the algorithmic aspects of nonnegative $C^2$ interpolation in the plane. Specifically, we provide an efficient algorithm to compute a nonnegative $C^2(\mathbb{R}^2)$ extension of $ f $ with norm within a universal constant factor of the least possible. We also provide an efficient algorithm to approximate the trace norm.

math.CA

$C^m$ Semialgebraic Sections Over the Plane

In this paper we settle the two-dimensional case of a conjecture involving unknown semialgebraic functions with specified smoothness. More precisely, we prove the following result: Let $\mathcal{H}$ be a semialgebraic bundle with respect to $C^m_{loc}\left( \mathbb{R}^{2},\mathbb{R}^{D}\right) .$ If $\mathcal{H}$ has a section, then it has a semialgebraic section.

math.CA

On the Shape Fields Finiteness Principle

In this paper, we improve the finiteness constant for the finiteness principles for $C^m(\mathbb{R}^n,\mathbb{R}^d)$ and $C^{m-1,1}(\mathbb{R}^n,\mathbb{R}^D)$ selection proven by Fefferman, Israel, and the second author and extend the more general shape fields finiteness principle to the vector-valued case.

math.FA

Nonnegative $C^2(\mathbb{R}^2)$ interpolation

In this paper, we prove two improved versions of the Finiteness Principle for nonnegative $ C^2(\mathbb{R}^2) $ interpolation, previously proven by Fefferman, Israel, and Luli. The first version sharpens the finiteness constant to $ 64 $, and the second version carries better computational practicality. Along the way, we also provide detailed construction of nonnegative $ C^2 $ interpolants in one-dimension, and prove the nonexistence of a bounded linear $ C^2 $-extension operator that preserves nonnegativity.

math.CA

Solutions to a System of Equations for $C^m$ Functions

Fix $m\geq 0$, and let $A=\left( A_{ij}\left( x\right) \right) _{1\leq i\leq N,1\leq j\leq M}$ be a matrix of semialgebraic functions on $\mathbb{R}^{n}$ or on a compact subset $E \subset \mathbb{R}^n$. Given $f=\left( f_{1},\cdots ,f_{N}\right) \in C^{\infty }\left( \mathbb{R}^{n},\mathbb{R}^{N}\right) $, we consider the following system of equations \begin{equation} \sum_{j=1}^{M}A_{ij}\left( x\right) F_{j}\left( x\right) =f_{i}\left( x\right) \text{ }\left( i=1,\cdots ,N\right) \text{.} \end{equation} In this paper, we give algorithms for computing a finite list of linear partial differential operators such that $AF= f$ admits a $C^m(\mathbb{R}^n, \mathbb{R}^M)$ solution $F=(F_1,\cdots, F_M)$ if and only if $f=(f_1,\cdots, f_N)$ is annihilated by the linear partial differential operators.

math.CA

Generators for the $C^m$-closures of Ideals

Let $\mathscr{R}$ denote the ring of real polynomials on $\mathbb{R}^{n}$. Fix $m\geq 0$, and let $A_{1},\cdots ,A_{M}\in \mathscr{R}$. The $ C^{m}$-closure of $\left( A_{1},\cdots ,A_{M}\right) $, denoted here by $ \left[ A_{1},\cdots ,A_{M};C^{m}\right] $, is the ideal of all $f\in \mathscr{R}$ expressible in the form $f=F_{1}A_{1}+\cdots +F_{M}A_{M}$ with each $F_{i}\in C^{m}\left( \mathbb{R}^{n}\right) $. In this paper we exhibit an algorithm to compute generators for $\left[ A_{1},\cdots ,A_{M};C^{m}\right] $.

math.CA

On one-dimension semi-linear wave equations with null conditions

It is well-known that in dimensions at least three semilinear wave equations with null conditions admit global solutions for small initial data. It is also known that in dimension two such result still holds for a certain class of quasi-linear wave equations with null conditions. The proofs are based on the decay mechanism of linear waves. However, in one dimension, waves do not decay. Nevertheless, we will prove that small data still lead to global solutions if the null condition is satisfied.

math.AP

On the generalized Buckley-Leverett equation

In this paper we study the generalized Buckley-Leverett equation with nonlocal regularizing terms. One of these regularizing terms is diffusive, while the other one is conservative. We prove that if the regularizing terms have order higher than one (combined), there exists a global strong solution for arbitrarily large initial data. In the case where the regularizing terms have combined order one, we prove the global existence of solution under some size restriction for the initial data. Moreover, in the case where the conservative regularizing term vanishes, regardless of the order of the diffusion and under certain hypothesis on the initial data, we also prove the global existence of strong solution and we obtain some new entropy balances. Finally, we provide numerics suggesting that, if the order of the diffusion is $0< α<1$, a finite time blow up of the solution is possible.

math.AP

Finitness Principles for Smooth Selection

In this paper we prove finiteness principles for $C^{m}\left( \mathbb{R}^{n}, \mathbb{R}^{D}\right) $-selection, and for $C^{m-1,1}\left( \mathbb{R}^{n}, \mathbb{R}^{D}\right) $-selection, in particular providing a proof for a conjecture of Brudyni-Shvartsman (1994) on Lipschitz selections for the case when the domain is $X = \mathbb{R}^n$.

math.FA

Interpolation of data by smooth non-negative functions

We prove a finiteness principle for interpolation of data by nonnegative Cm functions. Our result raises the hope that one can start to understand constrained interpolation problems in which e.g. the interpolating function F is required to be nonnegative.

math.CA

Finiteness Principles for Smooth Selection

In this paper we prove finiteness principles for $C^{m}\left( \mathbb{R}^{n}, \mathbb{R}^{D}\right) $-selection, and for $C^{m-1,1}\left( \mathbb{R}^{n}, \mathbb{R}^{D}\right) $-selection, in particular providing a proof for a conjecture of Brudyni-Shvartsman (1994) on Lipschitz selections for the case when the domain is $X = \mathbb{R}^n$. Our results raise the hope that one can start to understand constrained interpolation problems in which e.g. the interpolating function $F$ is required to be nonnegative everywhere.

math.CA

Fitting a Sobolev function to data

We exhibit an algorithm to solve the following extension problem: Given a finite set $E \subset \mathbb{R}^n$ and a function $f: E \rightarrow \mathbb{R}$, compute an extension $F$ in the Sobolev space $L^{m,p}(\mathbb{R}^n)$, $p>n$, with norm having the smallest possible order of magnitude, and secondly, compute the order of magnitude of the norm of $F$. Here, $L^{m,p}(\mathbb{R}^n)$ denotes the Sobolev space consisting of functions on $\mathbb{R}^n$ whose $m$th order partial derivatives belong to $L^p(\mathbb{R}^n)$. The running time of our algorithm is at most $C N \log N$, where $N$ denotes the cardinality of $E$, and $C$ is a constant depending only on $m$,$n$, and $p$.

math.CA