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Articles 1 - 9 of 9
Full-Text Articles in Physics
Accelerating Markov Chain Monte Carlo Sampling With Diffusion Models, N. T. Hunt-Smith, W. Melnitchouk, F. Ringer, N. Sato, A. W. Thomas, M. J. White
Accelerating Markov Chain Monte Carlo Sampling With Diffusion Models, N. T. Hunt-Smith, W. Melnitchouk, F. Ringer, N. Sato, A. W. Thomas, M. J. White
Physics Faculty Publications
Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions. We introduce a novel method for accelerating Markov Chain Monte Carlo (MCMC) sampling by pairing a Metropolis-Hastings algorithm with a diffusion model that can draw global samples with the aim of approximating the posterior. We briefly review diffusion models in the context of image synthesis before providing a streamlined diffusion model tailored towards low-dimensional data arrays. We then present our adapted Metropolis-Hastings algorithm which combines local proposals with global proposals taken from a diffusion model that is regularly trained on the samples produced during the …
Machine-Assisted Discovery Of Integrable Symplectic Mappings, T. Zolkin, Y. Kharkov, S. Nagaitsev
Machine-Assisted Discovery Of Integrable Symplectic Mappings, T. Zolkin, Y. Kharkov, S. Nagaitsev
Physics Faculty Publications
We present a new automated method for finding integrable symplectic maps of the plane. These dynamical systems possess a hidden symmetry associated with an existence of conserved quantities, i.e., integrals of motion. The core idea of the algorithm is based on the knowledge that the evolution of an integrable system in the phase space is restricted to a lower-dimensional submanifold. Limiting ourselves to polygon invariants of motion, we analyze the shape of individual trajectories thus successfully distinguishing integrable motion from chaotic cases. For example, our method rediscovers some of the famous McMillan-Suris integrable mappings and ultradiscrete Painlevé equations. In total, …
Machine Learning-Based Jet And Event Classification At The Electron-Ion Collider With Applications To Hadron Structure And Spin Physics, Kyle Lee, James Mulligan, Mateusz Płoskoń, Felix Ringer, Feng Yuan
Machine Learning-Based Jet And Event Classification At The Electron-Ion Collider With Applications To Hadron Structure And Spin Physics, Kyle Lee, James Mulligan, Mateusz Płoskoń, Felix Ringer, Feng Yuan
Physics Faculty Publications
We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in …
Coupled Dynamics Of Spin Qubits In Optical Dipole Microtraps: Application To The Error Analysis Of A Rydberg-Blockade Gate, L. V. Gerasimov, R. R. Yusupov, A. D. Moiseevsky, I. Vybornyi, K. S. Tikhonov, S. P. Kulik, S. S. Straupe, Charles I. Sukenik, D. V. Kupriyanov
Coupled Dynamics Of Spin Qubits In Optical Dipole Microtraps: Application To The Error Analysis Of A Rydberg-Blockade Gate, L. V. Gerasimov, R. R. Yusupov, A. D. Moiseevsky, I. Vybornyi, K. S. Tikhonov, S. P. Kulik, S. S. Straupe, Charles I. Sukenik, D. V. Kupriyanov
Physics Faculty Publications
Single atoms in dipole microtraps or optical tweezers have recently become a promising platform for quantum computing and simulation. Here we report a detailed theoretical analysis of the physics underlying an implementation of a Rydberg two-qubit gate in such a system—a cornerstone protocol in quantum computing with single atoms. We focus on a blockade-type entangling gate and consider various decoherence processes limiting its performance in a real system. We provide numerical estimates for the limits on fidelity of the maximally entangled states and predict the full process matrix corresponding to the noisy two-qubit gate. We consider different excitation geometries and …
Simulations Of Coherent Synchrotron Radiation On Parallel Hybrid Gpu/Cpu Platform, B. Terzić, K. Arumugam, D. Duffin, A. Godunov, T. Islam, D. Ranjan, S. Sangam, Mohammad Zubair
Simulations Of Coherent Synchrotron Radiation On Parallel Hybrid Gpu/Cpu Platform, B. Terzić, K. Arumugam, D. Duffin, A. Godunov, T. Islam, D. Ranjan, S. Sangam, Mohammad Zubair
Physics Faculty Publications
Coherent synchrotron radiation (CSR) is an effect of self-interaction of an electron bunch as it traverses a curved path. It can cause a significant emittance degradation, as well as fragmentation and microbunching. Numerical simulations of the 2D/3D CSR effects have been extremely challenging due to computational bottlenecks associated with calculating retarded potentials via integrating over the history of the bunch. We present a new high-performance 2D, particle-in-cell code which uses massively parallel multicore GPU/GPU platforms to alleviate computational bottlenecks. The code formulates the CSR problem from first principles by using the retarded scalar and vector potentials to compute the self-interaction …
Long-Term Simulations Of Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, R. Majeti, C. Cotnoir, M. Stefani, D. Ranjan, A. Godunov, V. Morozov, H. Zhang, F. Lin, Y. Roblin, E. Nissen, T. Satogata
Long-Term Simulations Of Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, R. Majeti, C. Cotnoir, M. Stefani, D. Ranjan, A. Godunov, V. Morozov, H. Zhang, F. Lin, Y. Roblin, E. Nissen, T. Satogata
Physics Faculty Publications
Future machines such as the electron-ion colliders (JLEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations which require millions of turns. Until recently, most of the methods used linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a sympletic way up to an arbitrary order and colliding them …
High-Fidelity Simulations Of Long-Term Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, M. Aturban, C. Cotnoir, A. Godunov, D. Ranjan, M. Stefani, M. Zubair, F. Lin, V. Morozov, Y. Roblin, H. Zhang
High-Fidelity Simulations Of Long-Term Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, M. Aturban, C. Cotnoir, A. Godunov, D. Ranjan, M. Stefani, M. Zubair, F. Lin, V. Morozov, Y. Roblin, H. Zhang
Physics Faculty Publications
Future machines such as the Electron Ion Collider (MEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations typically requiring millions of turns. Until recently, most of the methods have involved using linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a sympletic way up to an arbitrary order. …
High-Performance Simulations Of Coherent Synchrotron Radiation On Multicore Gpu And Cpu Platforms, B. Terzić, A. Godunov, K. Arumugam, D. Ranjan, M. Zubair
High-Performance Simulations Of Coherent Synchrotron Radiation On Multicore Gpu And Cpu Platforms, B. Terzić, A. Godunov, K. Arumugam, D. Ranjan, M. Zubair
Physics Faculty Publications
Coherent synchrotron radiation (CSR) is an effect of self-interaction of an electron bunch as it traverses a curved path. It can cause a significant emittance degradation and microbunching. We present a new high-performance 2D, particle-in-cell code which uses massively parallel multicore GPU/GPU platforms to alleviate computational bottlenecks. The code formulates the CSR problem from first principles by using the retarded scalar and vector potentials to compute the self-interaction fields. The speedup due to the parallel implementation on GPU/CPU platforms exceeds three orders of magnitude, thereby bringing a previously intractable problem within reach. The accuracy of the code is verified against …
Simultaneous Optimization Of The Cavity Heat Load And Trip Rates In Linacs Using A Genetic Algorithm, Balša Terzić, Alicia S. Hofler, Cody J. Reeves, Sabbir A. Khan, Geoffrey A. Krafft, Jay Benesch, Arne Freyberger, Desh Ranjan
Simultaneous Optimization Of The Cavity Heat Load And Trip Rates In Linacs Using A Genetic Algorithm, Balša Terzić, Alicia S. Hofler, Cody J. Reeves, Sabbir A. Khan, Geoffrey A. Krafft, Jay Benesch, Arne Freyberger, Desh Ranjan
Physics Faculty Publications
In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab's Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.