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We show a partial Boolean function $f$ together with an input $x\in f^{-1}\left(*\right)$ such that both $C_{\bar{0}}\left(f,x\right)$ and $C_{\bar{1}}\left(f,x\right)$ are at least $C\left(f\right)^{2-o\left(1\right)}$. Due to recent…

Computational Complexity · Computer Science 2021-03-10 Kaspars Balodis

The threshold degree of a function f:{0,1}^n->{-1,+1} is the least degree of a real polynomial p with f(x)=sgn p(x). We prove that the intersection of two halfspaces on {0,1}^n has threshold degree Omega(n), which matches the trivial upper…

Computational Complexity · Computer Science 2010-02-25 Alexander A. Sherstov

Nisan and Szegedy (CC 1994) showed that any Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ that depends on all its input variables, when represented as a real-valued multivariate polynomial $P(x_1,\ldots,x_n)$, has degree at least $\log…

Computational Complexity · Computer Science 2021-07-08 Srikanth Srinivasan , S. Venkitesh

The theorem states that: Every Boolean function can be $\epsilon -approximated$ by a Disjunctive Normal Form (DNF) of size $O_{\epsilon}(2^{n}/\log{n})$. This paper will demonstrate this theorem in detail by showing how this theorem is…

Computational Complexity · Computer Science 2020-05-13 Yunhao Yang , Andrew Tan

We prove that, to compute a Boolean function $f$ on $N$ variables with error probability $\epsilon$, any quantum black-box algorithm has to query at least $\frac{1 - 2\sqrt{\epsilon}}{2} \rho_f N = \frac{1 - 2\sqrt{\epsilon}}{2} \bar{S}_f$…

Quantum Physics · Physics 2007-05-23 Yaoyun Shi

We show that every real polynomial $f$ nonnegative on $[-1,1]^{n}$ can be approximated in the $l_{1}$-norm of coefficients, by a sequence of polynomials $\{f_{\ep r}\}$ that are sums of squares. This complements the existence of s.o.s.…

Algebraic Geometry · Mathematics 2007-05-23 Jean B. Lasserre , Tim Netzer

A simple way to generate a Boolean function is to take the sign of a real polynomial in $n$ variables. Such Boolean functions are called polynomial threshold functions. How many low-degree polynomial threshold functions are there? The…

Probability · Mathematics 2019-07-25 Pierre Baldi , Roman Vershynin

We give an explicit upper bound for the algebraic degree and an explicit lower bound for the absolute value of the minimum of a polynomial function on a compact connected component of a basic closed semialgebraic set when this minimum is…

Algebraic Geometry · Mathematics 2011-12-05 Gabriela Jeronimo , Daniel Perrucci , Elias Tsigaridas

Solutions to many important partial differential equations satisfy bounds constraints, but approximations computed by finite element or finite difference methods typically fail to respect the same conditions. Chang and Nakshatrala enforce…

Numerical Analysis · Mathematics 2024-03-14 Robert C. Kirby , Daniel Shapero

We study the footprint function, with respect to a monomial order, of complete intersection graded ideals in a polynomial ring with coefficients in a field. For graded ideals of dimension one, whose initial ideal is a complete intersection,…

Commutative Algebra · Mathematics 2019-06-07 Yuriko Pitones , Jose Martinez-Bernal , Rafael H. Villarreal

We study the probabilistic degree over reals of the OR function on $n$ variables. For an error parameter $\epsilon$ in (0,1/3), the $\epsilon$-error probabilistic degree of any Boolean function $f$ over reals is the smallest non-negative…

Computational Complexity · Computer Science 2022-11-24 Siddharth Bhandari , Prahladh Harsha , Tulasimohan Molli , Srikanth Srinivasan

We study the complexity of learning and approximation of self-bounding functions over the uniform distribution on the Boolean hypercube ${0,1}^n$. Informally, a function $f:{0,1}^n \rightarrow \mathbb{R}$ is self-bounding if for every $x…

Machine Learning · Computer Science 2019-06-04 Vitaly Feldman , Pravesh Kothari , Jan Vondrák

Motivated by conforming finite element methods for elliptic problems of second order, we analyze the approximation of the gradient of a target function by continuous piecewise polynomial functions over a simplicial mesh. The main result is…

Numerical Analysis · Mathematics 2018-03-07 Andreas Veeser

Based on the recent breakthrough of Huang (2019), we show that for any total Boolean function $f$, $\bullet \quad \mathrm{deg}(f) = O(\widetilde{\mathrm{deg}}(f)^2)$: The degree of $f$ is at most quadratic in the approximate degree of $f$.…

Quantum Physics · Physics 2020-10-27 Scott Aaronson , Shalev Ben-David , Robin Kothari , Shravas Rao , Avishay Tal

When implementing regular enough functions (e.g., elementary or special functions) on a computing system, we frequently use polynomial approximations. In most cases, the polynomial that best approximates (for a given distance and in a given…

Mathematical Software · Computer Science 2007-05-23 Nicolas Brisebarre , Jean-Michel Muller

The degree of a polynomial representing (or approximating) a function f is a lower bound for the number of quantum queries needed to compute f. This observation has been a source of many lower bounds on quantum algorithms. It has been an…

Quantum Physics · Physics 2008-05-12 Andris Ambainis

Let $E_n(f)_{\alpha,\beta,\gamma}$ denote the error of best approximation by polynomials of degree at most $n$ in the space $L^2(\varpi_{\alpha,\beta,\gamma})$ on the triangle $\{(x,y): x, y \ge 0, x+y \le 1\}$, where…

Classical Analysis and ODEs · Mathematics 2019-02-01 Han Feng , Christian Krattenthaler , Yuan Xu

The Fourier-Walsh expansion of a Boolean function $f \colon \{0,1\}^n \rightarrow \{0,1\}$ is its unique representation as a multilinear polynomial. The Kindler-Safra theorem (2002) asserts that if in the expansion of $f$, the total weight…

Combinatorics · Mathematics 2019-01-28 Nathan Keller , Ohad Klein

We consider approximating analytic functions on the interval $[-1,1]$ from their values at a set of $m+1$ equispaced nodes. A result of Platte, Trefethen \& Kuijlaars states that fast and stable approximation from equispaced samples is…

Numerical Analysis · Mathematics 2022-03-08 Ben Adcock , Alexei Shadrin

Let $E_n(f)_\mu$ be the error of best approximation by polynomials of degree at most $n$ in the space $L^2(\varpi_\mu, \mathbb{B}^d)$, where $\mathbb{B}^d$ is the unit ball in $\mathbb{R}^d$ and $\varpi_\mu(x) = (1-\|x\|^2)^\mu$ for $\mu >…

Classical Analysis and ODEs · Mathematics 2017-05-03 Miguel Pinar , Yuan Xu