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The Multilevel Monte Carlo (MLMC) method has been applied successfully in a wide range of settings since its first introduction by Giles (2008). When using only two levels, the method can be viewed as a kind of control-variate approach to…

Computational Finance · Quantitative Finance 2024-05-07 Yu Li , Antony Ware

We present a novel formulation of the vibrational density matrix renormalization group (vDMRG) algorithm tailored to strongly anharmonic molecules described by general high-dimensional model representations of potential energy surfaces. For…

Chemical Physics · Physics 2023-12-29 Nina Glaser , Alberto Baiardi , Markus Reiher

This paper is a summary of the theory of discrete embeddings introduced in [5]. A discrete embedding is an algebraic procedure associating a numerical scheme to a given ordinary differential equation. Lagrangian systems possess a…

Numerical Analysis · Mathematics 2016-01-20 Loïc Bourdin , Jacky Cresson , Isabelle Greff , Pierre Inizan

Markov decision models (MDM) used in practical applications are most often less complex than the underlying `true' MDM. The reduction of model complexity is performed for several reasons. However, it is obviously of interest to know what…

Optimization and Control · Mathematics 2019-09-18 Patrick Kern , Axel Simroth , Henryk Zähle

We prove a quantitative version of a result of Furstenberg and Deligne stating that the the diagonal of a multivariate algebraic power series with coefficients in a field of positive characteristic is algebraic. As a consequence, we obtain…

Number Theory · Mathematics 2013-09-20 Boris Adamczewski , Jason P. Bell

Aligning Multimodal Large Language Models (MLLMs) requires reliable reward models, yet existing single-step evaluators can suffer from lazy judging, exploiting language priors over fine-grained visual verification. While rubric-based…

Computation and Language · Computer Science 2026-05-12 Rui Liu , Dian Yu , Zhenwen Liang , Yucheng Shi , Tong Zheng , Runpeng Dai , Haitao Mi , Pratap Tokekar , Leoweiliang

M5-branes on an ADE singularity are described by certain six-dimensional "conformal matter" superconformal field theories. Their Higgs moduli spaces contain information about various dynamical processes for the M5s; however, they are not…

High Energy Physics - Theory · Physics 2017-11-27 Noppadol Mekareeya , Kantaro Ohmori , Hiroyuki Shimizu , Alessandro Tomasiello

Value decomposition has long been a fundamental technique in multi-agent dynamic programming and reinforcement learning (RL). Specifically, the value function of a global state $(s_1,s_2,\ldots,s_N)$ is often approximated as the sum of…

Machine Learning · Computer Science 2025-11-14 Shuze Chen , Tianyi Peng

We present the integrand reduction via multivariate polynomial division as a natural technique to encode the unitarity conditions of Feynman amplitudes. We derive a recursive formula for the integrand reduction, valid for arbitrary…

High Energy Physics - Phenomenology · Physics 2015-06-16 P. Mastrolia , E. Mirabella , G. Ossola , T. Peraro

We study four-derivative corrections to pure $\mathcal{N}=2$, $D=5$ gauged supergravity. In particular, we find that, up to field redefinitions, there is a single four-derivative superinvariant that one can add to the action, up to factors…

High Energy Physics - Theory · Physics 2022-06-15 James T. Liu , Robert J. Saskowski

Exponentiated gradient descent (EGD), a biologically motivated optimisation algorithm that respects Dale's law, produces log-normally distributed synaptic weights at convergence, in alignment with experimental observations in neuroscience.…

Machine Learning · Computer Science 2026-05-26 Nishanth Shetty , Madhava Prasath , Chandra Sekhar Seelamantula

We consider the one dimensional periodic complex valued mKdV, which corresponds to the first equation above cubic NLS in the associated integrable hierarchy. Our main result is the construction of a sequence of invariant measures supported…

Analysis of PDEs · Mathematics 2025-01-28 Carlos E. Kenig , Andrea R. Nahmod , Nataša Pavlović , Gigliola Staffilani , Nicola Visciglia

In this paper, we study the algebraic formula complexity of multiplying $d$ many $2\times 2$ matrices, denoted $\mathrm{IMM}_{d}$, and show that the well-known divide-and-conquer algorithm cannot be significantly improved at any depth, as…

Computational Complexity · Computer Science 2017-10-17 Suryajith Chillara , Nutan Limaye , Srikanth Srinivasan

In this paper, we show that the eigenvalues and eigenvectors of the spectral discretisation matrices resulted from the Legendre dual-Petrov-Galerkin (LDPG) method for the $m$th-order initial value problem (IVP): $u^{(m)}(t)=\sigma u(t),\,…

Numerical Analysis · Mathematics 2022-11-22 Desong Kong , Jie Shen , Li-Lian Wang , Shuhuang Xiang

In this paper we proceed to study properties of Mellin-Barnes (MB) transforms of Usyukina-Davydychev (UD) functions. In our previous papers [Nuclear Physics B 870 (2013) 243], [Nuclear Physics B 876 (2013) 322] we showed that multi-fold…

We study integrals of the form $\int_{\Omega}f\left( d\omega_1 , \ldots , d\omega_m \right), $ where $m \geq 1$ is a given integer, $1 \leq k_{i} \leq n$ are integers and $\omega_{i}$ is a $(k_{i}-1)$-form for all $1 \leq i \leq m$ and $…

Functional Analysis · Mathematics 2025-04-02 Swarnendu Sil

In this paper we introduce a new multilevel Monte Carlo (MLMC) estimator for multi-dimensional SDEs driven by Brownian motions. Giles has previously shown that if we combine a numerical approximation with strong order of convergence…

Computational Finance · Quantitative Finance 2014-05-19 Michael B. Giles , Lukasz Szpruch

In this paper, we present sufficient conditions and criteria to establish general large and moderate deviation principles for multivalued McKean-Vlasov stochastic differential equations (SDEs in short) by means of the weak convergence…

Probability · Mathematics 2025-07-10 Lingyan Cheng , Wei Liu , Huijie Qiao , Fengwu Zhu

The Lennard-Jones (LJ) potential is a cornerstone of Molecular Dynamics (MD) simulations and among the most widely used computational kernels in science. The potential models atomistic attraction and repulsion with century old prescribed…

We develop a new type of orthogonal polynomial, the modified discrete Laguerre (MDL) polynomials, designed to accelerate the computation of bosonic Matsubara sums in statistical physics. The MDL polynomials lead to a rapidly convergent…

Numerical Analysis · Mathematics 2021-01-06 Guanpeng Xu , Steven G. Johnson