Mining physical insight from time dependent many-body dynamics
Kyle Godbey
Slides with videos:
https://docs.google.com/presentation/d/1IFOChwaqHaGpoMOVSA0s3VEVCaZfD6q0LMsCSj-3hvo/edit?usp=sharing
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NP3M Seminar
March 27th, 2024
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Heavy-Ion Dynamics
Despite my focus on reactions, dynamics encompass a whole lot more!
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Real-Time Dynamics
Time-dependent, microscopic theories offer a rich depiction of the many complicated things nuclei might do within the characteristic nuclear timescale
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Video Credit: Aaron Philip
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Nuclei are more than blobs!
-> Neutron skins
-> Intrinsic deformations
-> Clustering effects
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K. Godbey, C Simenel, and A. S. Umar, Absence of hindrance in microscopic 12C + 12C fusion study, Phys. Rev. C 100, 024619 (2019)
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Correlations Between Structure and Reactions
Vbarrier is a quantity extracted from fusion cross sections
Nothing precludes a comparison to cross sections directly
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Structures in Reaction Data
Consider fusion cross sections for a chain of oxygen isotopes and carbon
R. T. deSouza, K. Godbey, S. Hudan, W. Nazarewicz, In search of beyond mean-field signatures in heavy-ion fusion reactions. (accepted) (2023)
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Structures in Reaction Data
L-wave ratcheting is present in both the theory and experiment, but other features are missing
The location of the barriers are relatively spot on!
R. T. deSouza, K. Godbey, S. Hudan, W. Nazarewicz, In search of beyond mean-field signatures in heavy-ion fusion reactions. (accepted) (2023)
PRELIMINARY
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March 27th, 2024
Structures in Reaction Data
R. T. deSouza, K. Godbey, S. Hudan, W. Nazarewicz, In search of beyond mean-field signatures in heavy-ion fusion reactions. (accepted) (2023)
L-wave ratcheting is present in both the theory and experiment, but other features are missing
The location of the barriers are relatively spot on!
NP3M |
NP3M Seminar
March 27th, 2024
Structures in Reaction Data
R. T. deSouza, K. Godbey, S. Hudan, W. Nazarewicz, In search of beyond mean-field signatures in heavy-ion fusion reactions. (accepted) (2023)
L-wave ratcheting is present in both the theory and experiment, but other features are missing
The location of the barriers are relatively spot on!
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March 27th, 2024
Transfer and Equilibration too!
K. Godbey, A. S. Umar, and C. Simenel, “Dependence of fusion on isospin dynamics”, Phys. Rev. C 95, 011601 (Rapid Communication) (2017).
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Transfer and Equilibration too!
C. Simenel, K. Godbey, and A. S. Umar, Timescales of Quantum Equilibration, Dissipation and Fluctuation in Nuclear Collisions, Phys. Rev. Lett. 124, 212504 (2020)
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Introducing Quasifission
That’s 10s of zeptoseconds!
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Deformed Shell Effects in
Quasifission
K. Godbey, A. S. Umar, and C. Simenel, “Deformed shell effects in 48Ca+249Bk quasifission fragments”, Phys. Rev. C 100, 024610 (2019).
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Quasifission as a Probe
for Fission
C. Simenel, P. McGlynn, A. S. Umar, and K. Godbey, “Comparison of fission and quasi-fission modes”, Physics Letters B 822, 136648 (2021).
Very similar shapes and dynamics are indeed seen in QF and fission, but to what extent?
Two excellent candidate systems to test/explore this:
48,49,50Ca + 176Yb -> Some QF
16,17,18O + 208Pb -> No QF
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Quasifission as a Probe
for Fission
C. Simenel, P. McGlynn, A. S. Umar, and K. Godbey, “Comparison of fission and quasi-fission modes”, Physics Letters B 822, 136648 (2021).
Quasifission as a surrogate for fission can be instrumental near the dripline, particularly in heavy nuclei
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Going to Superheavies
Given that quasifission dominates superheavy searches, that’s a natural direction to keep exploring
Figure credit: Richard Gumbel
PRELIMINARY
PRELIMINARY
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Enabling Progress
Explosion of interest in principled uncertainty quantification across nuclear physics in recent years
Now we can leverage that interest in collaboration with applied mathematicians, statisticians, and computer scientists
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Enabling Progress
For today, let’s consider model emulation and dimensionality reduction in general
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Current Ideas for Dynamics
Exploring multiple approaches, including Neural Implicit Flow and Fourier Neural Operators
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Current Ideas for Dynamics
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Current Ideas for Dynamics
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Coming Soon: NLDBench
To make all of this easier, we’re currently working on a benchmark suite for nonlinear dynamics – if you’ve got a use case, reach out!
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Always accepting new examples!
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Reproducibility and Accessibility
Image Credit:
J. D. McDonnell, N. Schunck, D. Higdon, J. Sarich, S. M. Wild, and W. Nazarewicz, Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements, Phys. Rev. Lett.114, 122501 (2015).
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Reproducibility and Accessibility
Y. Yamauchi, L. Buskirk, P. Giuliani, K. Godbey, Normalizing Flows for Bayesian Posteriors: Reproducibility and Deployment, (submitted) (2023).
A few challenges include:
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Reproducibility and Accessibility
Our approach: use an ML approach to learn normalizing flows for the high-dimensional posterior distributions
Y. Yamauchi, L. Buskirk, P. Giuliani, K. Godbey, Normalizing Flows for Bayesian Posteriors: Reproducibility and Deployment, (submitted) (2023).
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Reproducibility and Accessibility
Our approach: use an ML approach to learn normalizing flows for the high-dimensional posterior distributions
Y. Yamauchi, L. Buskirk, P. Giuliani, K. Godbey, Normalizing Flows for Bayesian Posteriors: Reproducibility and Deployment, (submitted) (2023).
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Y. Yamauchi, L. Buskirk, P. Giuliani, K. Godbey, Normalizing Flows for Bayesian Posteriors: Reproducibility and Deployment, (submitted) (2023).
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Other Avenues?
Something currently being explored is reducing the dimensionality of our model space for Bayesian model mixing
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Other Avenues?
Something currently being explored is reducing the dimensionality of our model space for Bayesian model mixing
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Path(s) Forward
Low-energy, heavy ion reactions are very likely to be informative for questions across the nuclear science community
Continued developments in time-dependent microscopic many-body theories are vital
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Path(s) Forward
Even more vital is a continued focus on accessibility of these advanced techniques
Consider getting involved and contributing materials, ideas, code, support, etc.
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Immense Gratitude to All Collaborators!
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Computing Resources
Australian National Computational Infrastructure Raijin and Gadi
Oak Ridge Leadership Computing Facility Summit and Frontier
Argonne Leadership Computing Facility Polaris
Texas A&M High Performance Research Computing Terra and Ada
Michigan State University HPCC
Funding
DOE NNSA Grant No. DE-NA0004074
DOE Grant Nos. DE-SC0013365, DE-SC0023175
NSF CSSI Program No. 2004601
Slide from Pablo Giuliani
~60 participants
spanning a wide audience
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Slide from Pablo Giuliani
Social, too!
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PRELIMINARY
Dimensionality Reduction
Fast
Accurate
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Infrastructure Development
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Challenges in UQ
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Challenges in UQ
In statistics:
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Case Study: Heavy-Ion Fusion
Near-barrier fusion reactions are filled with insights into the structure and dynamics of the systems of interest
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Case Study: Heavy-Ion Fusion
Barrier determination requires ~10s of time-dependent trajectories for each geometric configuration
Cross sections require 100s-1000s of evaluations
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Case Study: Heavy-Ion Fusion
Simulation times vary from a few hours for light systems to a few days for heavy systems
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Current Ideas for Dynamics
Exploring multiple approaches, including Neural Implicit Flow and Fourier Neural Operators
Now at Nvidia
Director of ML research at Nvidia
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Current Ideas for Dynamics
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Development of New Functionals
Complementary to efforts in UQ is the development of new energy density functionals
I’d classify this direction as model discovery
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Development of New Functionals
One approach to data-driven model discovery is in considering similar observables to UQ studies
The flexibility of DFT can be exploited, however, to pin down densities from ab initio methods via an inverse Kohn-Sham procedure
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Development of New Functionals
Density, 𝜌(r)
Nucleon localization function
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Needs for EDF Development
On the HPC, math, and stats side:
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Needs for EDF Development
On the physics side:
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Infrastructure Development
The glue that keeps the ship together: Infrastructure!
Infrastructure impacts every aspect of the research enterprise, from software development through final data distribution
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Infrastructure Development
Primary goal:
Improve data reproducibility and accessibility standards across the board
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Infrastructure Development
Benefits:
Documented, repeatable pipelines saves time
Traceable results with associated data used in calibration and ML applications
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Infrastructure Development
Benefits:
Increased accessibility and visibility of your results
Easier onboarding of new researchers
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Infrastructure Development
Benefits:
Easier to tie into other research workflows, fostering collaboration
Easier to more rapidly deploy results for user-focused applications
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Infrastructure Development
Current plan is to automate the model discovery elements of the pipeline to automatically build and test emulators for more expedient UQ
Also planned are continuous calibration runners that can agilely adapt to new experimental data
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Infrastructure Development
The technology that enables this are the (relatively) cheap and abundant cloud computing resources on the market
Cloud computing is a different paradigm from traditional HPC, but it shouldn’t be overlooked if you need something elastic and quickly scalable
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Infrastructure Development
What about other sources of data?
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Needs in Infrastructure
We’re always seeking inspiration in terms of DevOps/MLOps and how our workflows and deployments can be made more efficient and scalable
Cloud computing applications benefit from platform flexibility, so simultaneously (and efficiently) targeting multiple architectures can pay off
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Highlight | HFBFFT
Next generation 3D coordinate space DFT software with a focus on usability, flexibility, and platform independence
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Highlight | HFBFFT
Planned features include:
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Highlight | HFBFFT
Planned features in line with this talk include:
Stick around for Metin’s talk!
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The framework: Density Functional Theory
‘Microscopic’ method optimized for description of one-body observables
Fantastically extensible framework to go beyond base assumptions
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