Continuous-time Diffusion Monte Carlo and the Quantum Dimer Model

A continuous-time formulation of the Diffusion Monte Carlo method for lattice models is presented. In its simplest version, without the explicit use of trial wavefunctions for importance sampling, the method is an excellent tool for investigating quantum lattice models in parameter regions close to generalized Rokhsar-Kivelson points. This is illustrated by showing results for the quantum dimer model on both triangular and square lattices. The potential energy of two test monomers as a function of their separation is computed at zero temperature. The existence of deconfined monomers in the triangular lattice is confirmed. The method allows also the study of dynamic monomers. A finite fraction of dynamic monomers is found to destroy the confined phase on the square lattice when the hopping parameter increases beyond a finite critical value. The phase boundary between the monomer confined and deconfined phases is obtained.Comment: 4 pages, 4 figures, revtex; Added a figure showing the confinement/deconfinement phase boundary for the doped quantum dimer mode

A comparison of two magnetic ultra-cold neutron trapping concepts using a Halbach-octupole array

This paper describes a new magnetic trap for ultra-cold neutrons (UCNs) made from a 1.2 m long Halbach-octupole array of permanent magnets with an inner bore radius of 47 mm combined with an assembly of superconducting end coils and bias field solenoid. The use of the trap in a vertical, magneto-gravitational and a horizontal setup are compared in terms of the effective volume and ability to control key systematic effects that need to be addressed in high precision neutron lifetime measurements

Asymptotic entanglement capacity of the Ising and anisotropic Heisenberg interactions

We compute the asymptotic entanglement capacity of the Ising interaction ZZ, the anisotropic Heisenberg interaction XX + YY, and more generally, any two-qubit Hamiltonian with canonical form K = a XX + b YY. We also describe an entanglement assisted classical communication protocol using the Hamiltonian K with rate equal to the asymptotic entanglement capacity.Comment: 5 pages, 1 figure; minor corrections, conjecture adde

Guarantees of Riemannian Optimization for Low Rank Matrix Completion

We study the Riemannian optimization methods on the embedded manifold of low rank matrices for the problem of matrix completion, which is about recovering a low rank matrix from its partial entries. Assume $m$ entries of an $n\times n$ rank $r$ matrix are sampled independently and uniformly with replacement. We first prove that with high probability the Riemannian gradient descent and conjugate gradient descent algorithms initialized by one step hard thresholding are guaranteed to converge linearly to the measured matrix provided \begin{align*} m\geq C_\kappa n^{1.5}r\log^{1.5}(n), \end{align*} where $C_\kappa$ is a numerical constant depending on the condition number of the underlying matrix. The sampling complexity has been further improved to \begin{align*} m\geq C_\kappa nr^2\log^{2}(n) \end{align*} via the resampled Riemannian gradient descent initialization. The analysis of the new initialization procedure relies on an asymmetric restricted isometry property of the sampling operator and the curvature of the low rank matrix manifold. Numerical simulation shows that the algorithms are able to recover a low rank matrix from nearly the minimum number of measurements

Nonlinear nonlocal multicontinua upscaling framework and its applications

In this paper, we discuss multiscale methods for nonlinear problems. The main idea of these approaches is to use local constraints and solve problems in oversampled regions for constructing macroscopic equations. These techniques are intended for problems without scale separation and high contrast, which often occur in applications. For linear problems, the local solutions with constraints are used as basis functions. This technique is called Constraint Energy Minimizing Generalized Multiscale Finite Element Method (CEM-GMsFEM). GMsFEM identifies macroscopic quantities based on rigorous analysis. In corresponding upscaling methods, the multiscale basis functions are selected such that the degrees of freedom have physical meanings, such as averages of the solution on each continuum. This paper extends the linear concepts to nonlinear problems, where the local problems are nonlinear. The main concept consists of: (1) identifying macroscopic quantities; (2) constructing appropriate oversampled local problems with coarse-grid constraints; (3) formulating macroscopic equations. We consider two types of approaches. In the first approach, the solutions of local problems are used as basis functions (in a linear fashion) to solve nonlinear problems. This approach is simple to implement; however, it lacks the nonlinear interpolation, which we present in our second approach. In this approach, the local solutions are used as a nonlinear forward map from local averages (constraints) of the solution in oversampling region. This local fine-grid solution is further used to formulate the coarse-grid problem. Both approaches are discussed on several examples and applied to single-phase and two-phase flow problems, which are challenging because of convection-dominated nature of the concentration equation

An experimental study on a motion sensing system for sports training

In sports science, motion data collected from athletes is used to derive key performance characteristics, such as stride length and stride frequency, that are vital coaching support information. The sensors for use must be more accurate, must capture more vigorous events, and have strict weight and size requirements, since they must not themselves affect performance. These requirements mean each wireless sensor device is necessarily resource poor and yet must be capable of communicating a considerable amount of data, contending for the bandwidth with other sensors on the body. This paper analyses the results of a set of network traffic experiments that were designed to investigate the suitability of conventional wireless motion sensing system design � which generally assumes in-network processing - as an efficient and scalable design for use in sports training

Quality-of-service routing with two concave constraints

Routing is a process of finding a network path from a source node to a destination node. A good routing protocol should find the "best path" from a source to a destination. When there are independent constraints to be considered, the "best path" is not well-defined. In our previous work, we developed a line segment representation for Quality-of-Service routing with bandwidth and delay requirements. In this paper, we propose how to adopt the line segment when a request has two concave constraints. We have developed a series of operations for constructing routing tables under the distance-vector protocol. We evaluate the performance through extensive simulations. ©2008 IEEE.published_or_final_versio