Solving periodic semilinear stiff PDEs in 1D, 2D and 3D with exponential integrators

Dozens of exponential integration formulas have been proposed for the high-accuracy solution of stiff PDEs such as the Allen-Cahn, Korteweg-de Vries and Ginzburg-Landau equations. We report the results of extensive comparisons in MATLAB and Chebfun of such formulas in 1D, 2D and 3D, focusing on fourth and higher order methods, and periodic semilinear stiff PDEs with constant coefficients. Our conclusion is that it is hard to do much better than one of the simplest of these formulas, the ETDRK4 scheme of Cox and Matthews

A framework for cryptographic problems from linear algebra

We introduce a general framework encompassing the main hard problems emerging in lattice-based cryptography, which naturally includes the recently proposed Mersenne prime cryptosystem, but also problems coming from code-based cryptography. The framework allows to easily instantiate new hard problems and to automatically construct plausibly post-quantum secure primitives from them. As a first basic application, we introduce two new hard problems and the corresponding encryption schemes. Concretely, we study generalisations of hard problems such as SIS, LWE and NTRU to free modules over quotients of Z[X] by ideals of the form (f,g), where f is a monic polynomial and g∈Z[X] is a ciphertext modulus coprime to f. For trivial modules (i.e. of rank one), the case f=Xn+1 and g=q∈Z>1 corresponds to ring-LWE, ring-SIS and NTRU, while the choices f=Xn−1 and g=X−2 essentially cover the recently proposed Mersenne prime cryptosystems. At the other extreme, when considering modules of large rank and letting deg(f)=1, one recovers the framework of LWE and SIS

Efficiently processing complex-valued data in homomorphic encryption

We introduce a new homomorphic encryption scheme that is natively capable of computing with complex numbers. This is done by generalizing recent work of Chen, Laine, Player and Xia, who modified the Fan–Vercauteren scheme by replacing the integral plaintext modulus t by a linear polynomial X − b. Our generalization studies plaintext moduli of the form Xm + b. Our construction significantly reduces the noise growth in comparison to the original FV scheme, so much deeper arithmetic circuits can be homomorphically executed

A robust and adaptive GenEO-type domain decomposition preconditioner for H(curl)\mathbf{H}(\mathbf{curl}) problems in general non-convex three-dimensional geometries

In this paper we develop and analyse domain decomposition methods for linear systems of equations arising from conforming finite element discretisations of positive Maxwell-type equations, namely for $\mathbf{H}(\mathbf{curl})$ problems. It is well known that convergence of domain decomposition methods rely heavily on the efficiency of the coarse space used in the second level. We design adaptive coarse spaces that complement a near-kernel space made from the gradient of scalar functions. The new class of preconditioner is inspired by the idea of subspace decomposition, but based on spectral coarse spaces, and is specially designed for curl-conforming discretisations of Maxwell's equations in heterogeneous media on general domains which may have holes. Our approach has wider applicability and theoretical justification than the well-known Hiptmair-Xu auxiliary space preconditioner, with results extending to the variable coefficient case and non-convex domains at the expense of a larger coarse space

Can DtN and GenEO coarse spaces be sufficiently robust for heterogeneous Helmholtz problems?

Numerical solutions of heterogeneous Helmholtz problems present various computational challenges, with descriptive theory remaining out of reach for many popular approaches. Robustness and scalability are key for practical and reliable solvers in large-scale applications, especially for large wave number problems. In this work, we explore the use of a GenEO-type coarse space to build a two-level additive Schwarz method applicable to highly indefinite Helmholtz problems. Through a range of numerical tests on a 2D model problem, discretised by finite elements on pollution-free meshes, we observe robust convergence, iteration counts that do not increase with the wave number, and good scalability of our approach. We further provide results showing a favourable comparison with the DtN coarse space. Our numerical study shows promise that our solver methodology can be effective for challenging heterogeneous applications

On the Security of the Multivariate Ring Learning with Errors Problem

The Multivariate Ring Learning with Errors ($m$-RLWE) problem was introduced in 2015 by Pedrouzo-Ulloa, Troncoso-Pastoriza and Pérez-González. Instead of working over a polynomial residue ring with one variable as in RLWE, it works over a polynomial residue ring in several variables. However, care must be taken when choosing the multivariate rings for use in cryptographic applications as they can be either weak or simply equivalent to univariate RLWE. For example, Pedrouzo-Ulloa et al.\ suggest using tensor products of cyclotomic rings, in particular power-of-two cyclotomic rings. They claim incorrectly that the security increases with the product of the individual degrees. In this paper, we present simple methods to solve the search $m$-RLWE problem far more efficiently than is stated in the current literature by reducing the problem to the RLWE problem in dimension equal to the maximal degree of its components (and not the product) and where the noise increases with the square-root of the degree of the other components. Our methods utilise the fact that the defining cyclotomic polynomials share algebraically related roots. We use these methods to successfully attack the search variant of the $m$-RLWE problem for a set of parameters estimated to offer more than 2600 bits of security, and being equivalent to solving the bounded distance decoding problem in a highly structured lattice of dimension 16384, in less than two weeks of computation time or just a few hours if parallelized on 128 cores. Finally, we also show that optimizing module-LWE cryptosystems by introducing an extra ring structure as is common practice to optimize LWE, often results in a total breakdown of security

SoK: On the Security of Cryptographic Problems from Linear Algebra

There are two main aims to this paper. Firstly, we survey the relevant existing attack strategies known to apply to the most commonly used lattice-based cryptographic problems as well as to a number of their variants. In particular, we consider attacks against problems in the style of LWE, SIS and NTRU defined over rings of the form $\mathbb{Z}[X]/(f(X), g(X))$, where classically $g(X) = q$ is an integer modulus. We also include attacks on variants which use only large integer arithmetic, corresponding to the degree one case $g(X) = X - c$. Secondly, for each of these approaches we investigate whether they can be generalised to the case of a polynomial modulus $g(X)$ having degree larger than one, thus addressing the security of the generalised cryptographic problems from linear algebra introduced by Bootland et al. We find that some attacks readily generalise to a wide range of parameters while others require very specific conditions to be met in order to work