arXiv subjects

Meifeng Lin

Publications and source records attributed to Meifeng Lin.

At least 37 records · Page 2Linked to original sources

arXiv2022

Report of the Snowmass 2021 Topical Group on Lattice Gauge Theory

Lattice gauge theory continues to be a powerful theoretical and computational approach to simulating strongly interacting quantum field theories, whose applications permeate almost all disciplines of modern-day research in High-Energy Physics. Whether it is to enable precision quark- and lepton-flavor physics, to uncover signals of new physics in nucleons and nuclei, to elucidate hadron structure and spectrum, to serve as a numerical laboratory to reach beyond the Standard Model, or to invent and improve state-of-the-art computational paradigms, the lattice-gauge-theory program is in a prime position to impact the course of developments and enhance discovery potential of a vibrant experimental program in High-Energy Physics over the coming decade. This projection is based on abundant successful results that have emerged using lattice gauge theory over the years: on continued improvement in theoretical frameworks and algorithmic suits; on the forthcoming transition into the exascale era of high-performance computing; and on a skillful, dedicated, and organized community of lattice gauge theorists in the U.S. and worldwide. The prospects of this effort in pushing the frontiers of research in High-Energy Physics have recently been studied within the U.S. decadal Particle Physics Planning Exercise (Snowmass 2021), and the conclusions are summarized in this Topical Report.

hep-lat↗

arXiv2022

Methods and Results for Quantum Optimal Pulse Control on Superconducting Qubit Systems

The effective use of current Noisy Intermediate-Scale Quantum (NISQ) devices is often limited by the noise which is caused by interaction with the environment and affects the fidelity of quantum gates. In transmon qubit systems, the quantum gate fidelity can be improved by applying control pulses that can minimize the effects of the environmental noise. In this work, we employ physics-guided quantum optimal control strategies to design optimal pulses driving quantum gates on superconducting qubit systems. We test our results by conducting experiments on the IBM Q hardware using their OpenPulse API. We compare the performance of our pulse-optimized quantum gates against the default quantum gates and show that the optimized pulses improve the fidelity of the quantum gates, in particular the single-qubit gates. We discuss the challenges we encountered in our work and point to possible future improvements.

quant-ph↗

arXiv2022

Lattice QCD and the Computational Frontier

The search for new physics requires a joint experimental and theoretical effort. Lattice QCD is already an essential tool for obtaining precise model-free theoretical predictions of the hadronic processes underlying many key experimental searches, such as those involving heavy flavor physics, the anomalous magnetic moment of the muon, nucleon-neutrino scattering, and rare, second-order electroweak processes. As experimental measurements become more precise over the next decade, lattice QCD will play an increasing role in providing the needed matching theoretical precision. Achieving the needed precision requires simulations with lattices with substantially increased resolution. As we push to finer lattice spacing we encounter an array of new challenges. They include algorithmic and software-engineering challenges, challenges in computer technology and design, and challenges in maintaining the necessary human resources. In this white paper we describe those challenges and discuss ways they are being dealt with. Overcoming them is key to supporting the community effort required to deliver the needed theoretical support for experiments in the coming decade.

hep-lat↗

arXiv2022

Portability: A Necessary Approach for Future Scientific Software

Today's world of scientific software for High Energy Physics (HEP) is powered by x86 code, while the future will be much more reliant on accelerators like GPUs and FPGAs. The portable parallelization strategies (PPS) project of the High Energy Physics Center for Computational Excellence (HEP/CCE) is investigating solutions for portability techniques that will allow the coding of an algorithm once, and the ability to execute it on a variety of hardware products from many vendors, especially including accelerators. We think without these solutions, the scientific success of our experiments and endeavors is in danger, as software development could be expert driven and costly to be able to run on available hardware infrastructure. We think the best solution for the community would be an extension to the C++ standard with a very low entry bar for users, supporting all hardware forms and vendors. We are very far from that ideal though. We argue that in the future, as a community, we need to request and work on portability solutions and strive to reach this ideal.

physics.comp-ph↗

arXiv2022

DUNE Software and High Performance Computing

DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by modern high-performance computing facilities. In order to efficiently exploit these new architectures, particularly those with high CPU core counts and GPU accelerators, our existing software execution models require adaptation. In addition, the large size of individual units of raw data from the far detector modules pose an additional challenge somewhat unique to DUNE. Here we describe some of these problems and how we begin to solve them today with existing software frameworks and toolkits. We also describe ways we may leverage these existing software architectures to attack remaining problems going forward. This whitepaper is a contribution to the Computational Frontier of Snowmass21.

hep-ex↗

arXiv2022

Solving Simulation Systematics in and with AI/ML

Training an AI/ML system on simulated data while using that system to infer on data from real detectors introduces a systematic error which is difficult to estimate and in many analyses is simply not confronted. It is crucial to minimize and to quantitatively estimate the uncertainties in such analysis and do so with a precision and accuracy that matches those that AI/ML techniques bring. Here we highlight the need to confront this class of systematic error, discuss conventional ways to estimate it and describe ways to quantify and to minimize the uncertainty using methods which are themselves based on the power of AI/ML. We also describe methods to introduce a simulation into an AI/ML network to allow for training of its semantically meaningful parameters. This whitepaper is a contribution to the Computational Frontier of Snowmass21.

hep-ex↗

arXiv2021

Porting HEP Parameterized Calorimeter Simulation Code to GPUs

The High Energy Physics (HEP) experiments, such as those at the Large Hadron Collider (LHC), traditionally consume large amounts of CPU cycles for detector simulations and data analysis, but rarely use compute accelerators such as GPUs. As the LHC is upgraded to allow for higher luminosity, resulting in much higher data rates, purely relying on CPUs may not provide enough computing power to support the simulation and data analysis needs. As a proof of concept, we investigate the feasibility of porting a HEP parameterized calorimeter simulation code to GPUs. We have chosen to use FastCaloSim, the ATLAS fast parametrized calorimeter simulation. While FastCaloSim is sufficiently fast such that it does not impose a bottleneck in detector simulations overall, significant speed-ups in the processing of large samples can be achieved from GPU parallelization at both the particle (intra-event) and event levels; this is especially beneficial in conditions expected at the high-luminosity LHC, where extremely high per-event particle multiplicities will result from the many simultaneous proton-proton collisions. We report our experience with porting FastCaloSim to NVIDIA GPUs using CUDA. A preliminary Kokkos implementation of FastCaloSim for portability to other parallel architectures is also described.

hep-ex↗

arXiv2021

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computing-heavy tasks to specialized hardware. However, as the landscape of the compute accelerators is evolving fast, it becomes more and more difficult to manually adapt the code constantly to the latest hardware or software environments. A solution which is portable to multiple hardware architectures while not substantially compromising performance would be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we will present our experience porting the LArTPC simulation code in the Wire-Cell toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs will be presented, followed by a discussion of the factors affecting the performance and plans for future improvements.

cs.DC↗

arXiv2020

Augmented Signal Processing in Liquid Argon Time Projection Chambers with a Deep Neural Network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for comprehensive reconstruction of event topologies. In current-generation LArTPCs, the recorded data consist of digitized waveforms on wires produced by induced signal on wires of drifting ionization electrons, which can also be viewed as two-dimensional (2D) (time versus wire) projection images of charged-particle trajectories. For such an imaging detector, one critical step is the signal processing that reconstructs the original charge projections from the recorded 2D images. For the first time, we introduce a deep neural network in LArTPC signal processing to improve the signal region of interest detection. By combining domain knowledge (e.g., matching information from multiple wire planes) and deep learning, this method shows significant improvements over traditional methods. This work details the method, software tools, and performance evaluated with realistic detector simulations.

physics.ins-det↗

arXiv2020

Nucleon mass and isovector couplings in 2+1-flavor dynamical domain-wall lattice QCD near physical mass

We report nucleon mass, isovector vector and axial-vector charges, and tensor and scalar couplings, calculated using two recent 2+1-flavor dynamical domain-wall fermions lattice-QCD ensembles generated jointly by the RIKEN-BNL-Columbia and UKQCD collaborations. These ensembles were generated with Iwasaki $\times$ dislocation-suppressing-determinant-ratio gauge action at inverse lattice spacing of 1.378(7) GeV and pion mass values of 249.4(3) and 172.3(3) MeV. The nucleon mass extrapolates to a value $m_N = 0.950(5)$ GeV at physical point. The isovector vector charge renormalizes to unity in the chiral limit, narrowly constraining excited-state contamination in the calculation. The ratio of the isovector axial-vector to vector charges shows a deficit of about ten percent. The tensor coupling no longer depends on mass and extrapolates to 1.04(5) in $\overline {\rm MS}$ 2-GeV renormalization at physical point, in a good agreement with the value obtained at the lightest mass in our previous calculations and other calculations that followed. The scalar charge, though noisier, does not show mass dependence and is in agreement with other calculations.

hep-lat↗

arXiv2018

High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs

Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scientific computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We find that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of $10$ to $10^3$ depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.

physics.comp-ph↗

arXiv2017

Performance Portability Strategies for Grid C++ Expression Templates

One of the key requirements for the Lattice QCD Application Development as part of the US Exascale Computing Project is performance portability across multiple architectures. Using the Grid C++ expression template as a starting point, we report on the progress made with regards to the Grid GPU offloading strategies. We present both the successes and issues encountered in using CUDA, OpenACC and Just-In-Time compilation. Experimentation and performance on GPUs with a SU(3)$\times$SU(3) streaming test will be reported. We will also report on the challenges of using current OpenMP 4.x for GPU offloading in the same code.

hep-lat↗

arXiv2016

Nucleon structure from 2+1-flavor dynamical DWF ensembles

Nucleon isovector vector- and axialvector-current form factors, the renormalized isovector transversity and scalar charge, and the bare quark momentum and helicity moments of isovector structure functions are reported with improved statistics from two recent RBC+UKQCD 2+1-flavor dynamical domain-wall fermions ensembles: Iwasaki$\times$DSDR gauge $32^3\times64$ at inverse lattice spacing of 1.38 GeV and pion mass of 249 and 172 MeV.

hep-lat↗

arXiv2015

Optimizing the domain wall fermion Dirac operator using the R-Stream source-to-source compiler

The application of the Dirac operator on a spinor field, the Dslash operation, is the most computation-intensive part of the lattice QCD simulations. It is often the key kernel to optimize to achieve maximum performance on various platforms. Here we report on a project to optimize the domain wall fermion Dirac operator in Columbia Physics System (CPS) using the R-Stream source-to-source compiler. Our initial target platform is the Intel PC clusters. We discuss the optimization strategies involved before and after the automatic code generation with R-Stream and present some preliminary benchmark results.

hep-lat↗

arXiv2014

Composite bosonic baryon dark matter on the lattice: SU(4) baryon spectrum and the effective Higgs interaction

We present the spectrum of baryons in a new SU(4) gauge theory with fundamental fermion constituents. The spectrum of these bosonic baryons is of significant interest for composite dark matter theories. Here, we compare the spectrum and properties of SU(3) and SU(4) baryons, and then compute the dark-matter direct detection cross section via Higgs boson exchange for TeV-scale composite dark matter arising from a confining SU(4) gauge sector. Comparison with the latest LUX results leads to tight bounds on the fraction of the constituent-fermion mass that may arise from electroweak symmetry breaking. Lattice calculations of the dark matter mass spectrum and the Higgs-dark matter coupling are performed on quenched $16^{3} \times 32$, $32^{3} \times 64$, $48^{3} \times 96$, and $64^{3} \times128$ lattices with three different lattice spacings, using Wilson fermions with moderate to heavy pseudoscalar meson masses. Our results lay a foundation for future analytic and numerical study of composite baryonic dark matter.

hep-lat↗

arXiv2014

Nucleon Form Factors with 2+1 Flavors of Domain Wall Fermions and All-Mode-Averaging

We report recent progress in the calculations of the isovector nucleon electromagnetic form factors using 2+1 flavors of domain wall fermions at pion masses of 170 MeV and 250 MeV. The lattice size is fixed at $32^3\times64$ with a lattice cutoff scale of 1.37(1) GeV. For the calculations with $M_π= 170$ MeV, we employed the All-Mode-Averaging (AMA) technique, which led to roughly a factor of 20 improvement in computational efficiency and has reduced the statistical errors in our results significantly. We were also able to do calculations at two different source-sink separations, at roughly 1.3 fm and 1.0 fm, without much additional cost by reusing the low eigen-modes stored for the AMA calculations. We will present results for the isovector form factors and their derived quantities, including the Dirac and Pauli radii, anomalous magnetic moment and discuss the effects of possible excited-state contaminations. Connected contributions to the isoscalar Dirac and Pauli form factors will also be shown.

hep-lat↗

arXiv2013

Status of nucleon structure calculations with 2+1 flavors of domain wall fermions

We report the status of our nucleon structure calculations with 2+1 flavors of domain wall fermions on the RBC-UKQCD $32^3\times64$ gauge ensembles with the Iwasaki+DSDR action. These ensembles have a fixed lattice scale of 1/a = 1.37 GeV, and two pion masses of about 170 and 250 MeV. Preliminary results for the isovector electromagnectic form factors and their corresponding root-mean-squared (r.m.s.) radii will be presented.

hep-lat↗

arXiv2012

Finite-size scaling in nucleon axial charge from 2+1-flavor DWF lattice QCD

We report the current status of the on-going lattice-QCD calculations of nucleon isovector axial charge, g_A, using the RBC/UKQCD 2+1-flavor dynamical domain-wall fermion ensembles at lattice cutoff of about a^{-1}=1.4 GeV in a spatial volume (L = 4.6 fm)^3. The result from the ensemble with m_π= 250 MeV pion mass, corresponding to the finite-size scaling parameter m_πL \sim 5.8, agrees well with an earlier result at a^{-1}=1.7 GeV, L = 2.8 fm, and m_π= 420 MeV, with similar m_πL. This suggests the systematic error from excited-state contamination is small in both ensembles and about 10-% deficit in g_A we are observing is likely a finite-size effect that scales with m_πL. We also report the result from the lighter, m_π= 170 MeV ensemble.

hep-lat↗