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We consider the problem of searching a general $d$-dimensional lattice of $N$ vertices for a single marked item using a continuous-time quantum walk. We demand locality, but allow the walk to vary periodically on a small scale. By…

Quantum Physics · Physics 2014-09-08 Andrew M. Childs , Yimin Ge

Given a weighted graph $G$, a $(\beta,\varepsilon)$-hopset $H$ is an edge set such that for any $s,t \in V(G)$, where $s$ can reach $t$ in $G$, there is a path from $s$ to $t$ in $G \cup H$ which uses at most $\beta$ hops whose length is in…

Data Structures and Algorithms · Computer Science 2024-07-16 Vikrant Ashvinkumar , Aaron Bernstein , Chengyuan Deng , Jie Gao , Nicole Wein

We study the graph-theoretic properties of the trace of random walks on pseudorandom graphs. We show that for any $\varepsilon>0$, there exists a constant $C$ such that the cover time of an $(n,d,\lambda)$-graph $G$ with $d/\lambda\ge C$ is…

Combinatorics · Mathematics 2026-02-12 Yaobin Chen , Yiting Wang

Consider~\(n\) nodes~\(\{X_i\}_{1 \leq i \leq n}\) independently distributed in the unit square~\(S,\) each according to a distribution~\(f.\) Nodes~\(X_i\) and~\(X_j\) are joined by an edge if the Euclidean distance~\(d(X_i,X_j)\) is less…

Probability · Mathematics 2021-03-02 Ghurumuruhan Ganesan

Accurate measurements of K, D and B meson mixing amplitudes provide stringent constraints in the Unitary Triangle analysis, as well as useful bounds on New Physics scales. Lattice QCD provides a non perturbative tool to compute the hadronic…

High Energy Physics - Lattice · Physics 2014-11-11 Nuria Carrasco

Finding the global minimum of a multivariate function efficiently is a fundamental yet difficult problem in many branches of theoretical physics and chemistry. However, we observe that there are many physical systems for which the…

High Energy Physics - Lattice · Physics 2014-11-20 Dhagash Mehta , Andre Sternbeck , Lorenz von Smekal , Anthony G Williams

By investigating a parity and time-reversal (PT) symmetric, $N$-site lattice with impurities $\pm i\gamma$ and hopping amplitudes $t_0 (t_b)$ for regions outside (between) the impurity locations, we probe the origin of maximal PT-symmetry…

Quantum Physics · Physics 2015-05-30 Yogesh N. Joglekar , Jacob L. Barnett

We consider a discrete time random walk in one dimension. At each time step the walker jumps by a random distance, independent from step to step, drawn from an arbitrary symmetric density function. We show that the expected positive maximum…

Statistical Mechanics · Physics 2009-11-11 Alain Comtet , Satya N. Majumdar

In this paper, we focus on the following testing problem: assume that we are given observations of a real-valued signal along the grid $0,1,\ldots,N-1$, corrupted by white Gaussian noise. We want to distinguish between two hypotheses: (a)…

Statistics Theory · Mathematics 2015-06-02 Anatoli Juditsky , Arkadi Nemirovski

This work investigates linear precoding over non-singular linear channels with additive white Gaussian noise, with lattice-type inputs. The aim is to maximize the minimum distance of the received lattice points, where the precoder is…

Information Theory · Computer Science 2012-04-10 D. Kapetanovic , H. V. Cheng , W. H. Mow , F. Rusek

A new lower bound on the average reconstruction error variance of multidimensional sampling and reconstruction is presented. It applies to sampling on arbitrary lattices in arbitrary dimensions, assuming a stochastic process with constant,…

Information Theory · Computer Science 2018-06-19 Erik Agrell , Balázs Csébfalvi

Recently, the stability of certain topological phases of matter under weak perturbations was proven. Here, we present a short, alternate proof of the same result. We consider models of topological quantum order for which the unperturbed…

Mathematical Physics · Physics 2015-05-18 S. Bravyi , M. B. Hastings

Spontaneous symmetry breaking is a cornerstone of modern physics, defining a wealth of phenomena in condensed-matter and high-energy physics, and beyond. It requires an infinite number of degrees of freedom, and even then, for continuous…

Disordered Systems and Neural Networks · Physics 2026-04-10 Oleg Evnin

The 2D Discrete Gaussian model gives each height function $\eta : \mathbb{Z}^2\to\mathbb{Z}$ a probability proportional to $\exp(-\beta \mathcal{H}(\eta))$, where $\beta$ is the inverse-temperature and $\mathcal{H}(\eta) = \sum_{x\sim…

Probability · Mathematics 2014-05-22 Eyal Lubetzky , Fabio Martinelli , Allan Sly

We derive a lower bound on the smallest singular value of a random $d$-regular matrix, that is, the adjacency matrix of a random $d$-regular directed graph. More precisely, let $C_1<d< c_1 n/\log^2 n$ and let $\mathcal{M}_{n,d}$ be the set…

We introduce a Hamiltonian lattice model for the $(1+1)$-dimensional $\text{SU}(N_c)$ gauge theory coupled to one adjoint Majorana fermion of mass $m$. The discretization of the continuum theory uses staggered Majorana fermions. We analyze…

High Energy Physics - Theory · Physics 2024-05-02 Ross Dempsey , Igor R. Klebanov , Silviu S. Pufu , Benjamin T. Søgaard

Let $\mathcal G\subset L^2(\mathbb R)$ be the subspace spanned by a Gabor Riesz sequence $(g,\Lambda)$ with $g\in L^2(\mathbb R)$ and a lattice $\Lambda\subset\mathbb R^2$ of rational density. It was shown recently that if $g$ is…

Functional Analysis · Mathematics 2021-06-04 Andrei Caragea , Dae Gwan Lee , Friedrich Philipp , Felix Voigtlaender

These lectures provide an introduction to lattice methods for nonperturbative studies of Quantum Chromodynamics. Lecture 1 (Ch. 2): Basic techniques for QCD and results for hadron spectroscopy using the simplest discretizations; lecture 2…

High Energy Physics - Phenomenology · Physics 2016-09-06 T. DeGrand

We present the results of our lattice QCD computation of the hadronic matrix elements relevant to the $h_{c}\to \eta_{c}\gamma$ and $h_{b}\to \eta_{b}\gamma$ decays by using the gauge configurations produced by the Extended Twisted Mass…

High Energy Physics - Lattice · Physics 2025-04-24 D. Bečirević , R. Di Palma , R. Frezzotti , G. Gagliardi , V. Lubicz , F. Sanfilippo , N. Tantalo

Classical optimisation theory guarantees monotonic objective decrease for gradient descent (GD) when employed in a small step size, or ``stable", regime. In contrast, gradient descent on neural networks is frequently performed in a large…

Machine Learning · Computer Science 2025-10-21 Lachlan Ewen MacDonald , Hancheng Min , Leandro Palma , Salma Tarmoun , Ziqing Xu , René Vidal