Bulletin of the American Physical Society
APS April Meeting 2018
Volume 63, Number 4
Saturday–Tuesday, April 14–17, 2018; Columbus, Ohio
Session B14: Computational Physics |
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Sponsoring Units: DCOMP Chair: Alexei Bazavov, Michigan State University Room: A226 |
Saturday, April 14, 2018 10:45AM - 10:57AM |
B14.00001: Distributed Memory Techniques for Classical Simulation of Quantum Circuits Ryan LaRose We describe, implement, and test the performance of distributed memory simulations of quantum circuits on the MSU Laconia Top500 supercomputer. Using OpenMP and MPI hybrid parallelization, we first use a distributed matrix-vector multiplication with one-dimensional partitioning and discuss the shortcomings of this method due to the exponential memory requirements in simulating quantum computers. We then describe a more efficient method that stores only the $2^n$ amplitudes of the $n$ qubit state vector $|\psi\rangle$ and optimize its single node performance. In our multi-node implementation, we use a single amplitude communication protocol that maximizes the number of qubits able to be simulated and minimizes the ratio of qubits that require communication to those that do not, and we present an algorithm for efficiently determining communication pairs among processors. We simulate up to 30 qubits on a single node and 33 qubits with the state vector partitioned across 64 nodes. Lastly, we discuss the advantages and disadvantages of our communication scheme, propose potential improvements, and describe other optimizations such as storing the state vector non-sequentially in memory to map communication requirements to idle qubits in the circuit. [Preview Abstract] |
Saturday, April 14, 2018 10:57AM - 11:09AM |
B14.00002: Spectral Methods in the Presence of Discontinuities Jonah Miller, Piotrowska Joanna, Erik Schnetter Spectral methods provide an elegant and efficient way of numerically solving differential equations of all kinds. For smooth problems, truncation error for spectral methods vanishes exponentially in the infinity norm and $L_2$-norm. However, for non-smooth problems, convergence is significantly worse---the $L_2$-norm of the error for a discontinuous problem will converge at a sub-linear rate and the infinity norm will not converge at all. We explore and improve upon a post-processing technique---optimally convergent mollifiers---to recover exponential convergence from a poorly-converging spectral reconstruction of non-smooth data. [Preview Abstract] |
Saturday, April 14, 2018 11:09AM - 11:21AM |
B14.00003: Relaxation in the beta-FPUT chain for small N Tyler Barrett, Surajit Sen The study of the dynamics of the Fermi-Pasta-Ulam-Tsingou (FPUT) chain remains a challenging problem. Inspired by the recent work of Onorato et al. (PNAS 112, 4208 (2015)) on thermalization in the FPUT system, we report a study of relaxation processes in a 2-body FPUT system in the canonical ensemble, with comments on 3- and 4-body systems as well. The study demonstrates an application of the Recurrence Relations Method (RRM) introduced by Zwanzig, Mori, Lee and others to weakly nonlinear FPUT systems. We have obtained the first 200 levels of the continued fraction representation of the Laplace transformed momentum autocorrelation function (ACF) for the 2-body system. The ACF resulting from RRM techniques is shown for several system configurations and compared against numerical simulation in order to evaluate the efficacy of the RRM in these regimes, showing good agreement for short time scales. [Preview Abstract] |
Saturday, April 14, 2018 11:21AM - 11:33AM |
B14.00004: Studying chaotic pendulum using a microcontroller Cahit Erkal We propose a more efficient way of studying the complex motion of a double-pendulum by utilizing a microcontroller. This methodology, unlike many chaotic pendulums built for studying nonlinear dynamical properties of oscillating systems, offers a direct and precise control of the motion of the pendulum. A microcontroller and a motor drive the pendulums with any driving force that the user can chose. The pendulum consists of two light wooden bars connected with a very low friction bearing and it is driven directly by a low-power dc motor. What makes this pendulum appealing is its precision and simplicity. We also tested a video-based algorithm (Tracker, open source physics, https://physlets.org/tracker/) and Mathematica to collect the position data for analyses. [Preview Abstract] |
Saturday, April 14, 2018 11:33AM - 11:45AM |
B14.00005: Dynamics of high-density uniform ellipsoidal electron bunches driven by a linear chirp Xukun Xiang, Brandon Zerbe, Phillip Duxbury Understanding the focusing process of electron bunches after an RF cavity is important for designing ultrafast electron microscopy beamlines. A simple mean-field model is proposed for nonrelativistic compression of uniformly charged ellipsoids driven by initial linear chirp. Results from this model are compared with N-body simulations enabling a precise characterization of space charge effects near the focal point of the beam. [Preview Abstract] |
Saturday, April 14, 2018 11:45AM - 11:57AM |
B14.00006: Potts Model with Different Spin States, Simulated on a Structural Connectome to Model the Structure- Function Relationship of the Human Brain Pubuditha Abeyasinghe, Francisco de Sousa Lima, Marco Aiello, Carlo Cavaliere, Raimundo Costa, Adrian Owen, Andrea Soddu High complexity of the brain is strongly limiting our understanding of the mechanisms that dominate its functionality. It is believed that the spatial functional patterns could be at least partially understood by looking at the distribution of axonal fibers This was investigated by simulating models like the 2-dimensional (2D) classical Ising model on a structural connectome. 2D Ising model consists of two state spins and the Potts model is a generalized classical Ising model where we can explore the effect of spins with different number of states without limiting to two In this work, we have simulated the Potts model on a structural connectome with different number of spin states. Results from the model were compared with the empirical functional data to find an instant of the model that gives the best match. 2 states Potts model resulted in similar results to that of the Ising model. Additionally, thermodynamic properties such as the magnetic susceptibility, illustrated a phase transition from at the critical temperature for all cases. However, further analysis shows that a Potts model with 3 or 4 states spins not necessarily provide more information about the spontaneous function of the brain compared to the 2D classical Ising model. [Preview Abstract] |
Saturday, April 14, 2018 11:57AM - 12:09PM |
B14.00007: Quantum machine learning for universal quantum computation Elizabeth Behrman We describe a systematic method, using machine learning, to ``program'' a large-scale quantum computer. Large-scale quantum computational tasks require that the quantum computer be prepared in states which are multiply entangled; our methods show a way to create GHZ states over hundreds of qubits, and also to tailor the particular entanglement desired for a particular computation. In addition, current algorithmic approaches use a ``building block'' strategy, in which a procedure is formulated as a sequence of steps from a universal set, e.g., a sequence of CNOT, Hadamard, and phase shift gates. Using quantum learning enables us to perform computations without breaking down an algorithm into its ``building blocks'', eliminating a difficult step and potentially increasing efficiency by simplifying and reducing unnecessary complexity. Moreover, we demonstrate robustness of quantum learning to noise and to decoherence. [Preview Abstract] |
Saturday, April 14, 2018 12:09PM - 12:21PM |
B14.00008: Method of and System for Determining a Highly Accurate and Objective Maximum Medical Improvement Status and Dating Assignment Jerry Artz, Daniel Penn, John Alchemy We have developed a unique medical-physics computational algorithm to determine Maximum Medical Improvement (MMI) for a biological data set and consequent functional recovery. MMI occurs when an injured individual has received all available treatment and no further improvement is anticipated in the next one year. When the date of MMI is determined, permanent impairment may then be assigned providing the value of the injury's permanent functional loss. This loss is realized in percent of whole person impairment ({\%}WPI) as the convention set forth by the American Medical Association's \textit{Guides to the Evaluation of Permanent~}\textit{Impairment }(\textit{AMA's}~Guides). The present system for determining MMI status on an injured individual is highly subjective and variable across medial evaluators resulting in additional massive costs of delay along with costs of societal and business corrective action. The algorithm discussed gives a clear, innovative, methodical, and objective solution. This work is an interdisciplinary collaboration between the medical field and physics community. [Preview Abstract] |
Saturday, April 14, 2018 12:21PM - 12:33PM |
B14.00009: Spectral Clustering using Expert Knowledge C. Tyler Diggans We present results from an application of spectral clustering in which an algorithmically defined similarity measure is used in the domain of space object tracking. The current literature generally uses Gaussian kernels, which are well suited for Euclidean spaces, but the techniques could be more widely implemented in novel applications where expert knowledge and heuristics are required. Defining an algorithmic similarity measure allows such knowledge to be incorporated, which can be useful in a wide set of contexts. We show results for classifying space observations by object and present some theoretical justifications for its use. Advances in spectral clustering are utilized such as the use of a diffusion map to determine a low dimensional Euclidean representation of the data, which retains the non-linear associations, along with self-tuning parameters and the use of a local scaling to enhance results. Overall, this is meant to be an introduction to a set of classification tools through an example application. [Preview Abstract] |
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