Plasma Physics

Scientific Leader: Dr. John Verboncoeur

Theoretical and computational plasma physics, with a broad range of applications spanning from low temperature plasmas for lighting, thrusters and materials processing to hot plasmas for fusion; from ultra-cold plasmas to particle accelerators; from beams to pulsed power; and from intense kinetic nonequilibrium plasmas to high power microwaves.

Scientific Leader: Dr. Michael Murillo

Our group is involved in the two seemingly disparate research directions of computational plasma physics and agent-based modeling. In both cases, we employ computational methods for interacting many-body systems to understand the collective dynamics of the systems we study.

Scientific Leader: Dr. Min Chen

MSU Computational Seismology Lab works on analyzing, numerical modeling, and full waveform inversion of seismic array data from various sources, such as earthquakes, explosions, and ambient noise sources. Our goal is to better understand dynamic processes of the Earth on different time and spatial scales.

Scientific Leader: Dr. Arjun Krishnan

The Krishnan lab develops genomics/computational approaches to gain more nuanced and accurate insights into how our genome relates to health and disease. Combining statistics/machine-learning with large-scale genomic/clinical data, we build models and predictions about the genetic basis of biomedical phenomena, especially in an age-, sex-, and tissue-specific manner. Our overarching goal is to use these methods and insights to transform our ability to link an individual's genomic profiles to her/his physiological traits, disease risks, and clinical outcomes.

Scientific Leader: Dr. Matthew Hirn

The CEDAR team works at the interface of harmonic analysis and machine learning. We develop tools that uncover complex, multiscale patterns in high dimensional data by considering the underlying data geometries, invariants, hierarchies and statistics. Our focus is on rigorous mathematical theory coupled with state of the art numerical results in application specific domains. Research areas include:

• Wavelet theory and deep learning (scattering transforms)
• Diffusion based manifold learning 
• Smooth (Whitney) extensions and interpolations of data
• Many body problems in quantum chemistry
• Analysis of bio-medical data 

The Murillo Group has recently released a new paper published by The Journal of Statistical Physics on August, 2017 about Conservative, Entropic Multispecies BGK Model.

Link: https://link.springer.com/article/10.1007/s10955-017-1824-9

CMSE Professor Mohsen Zayernouri, the director of FMATH group, is publishing a new paper in Computer Methods in Applied Mechanics and Engineering on September 1, 2017.

Link: http://www.sciencedirect.com/science/article/pii/S0045782516312725

CMSE Professor Mohsen Zayernouri, the director of FMATH group, is publishing a new paper in SIAM Journal of Scientific Computing on 25 May 2017

Link: https://doi.org/10.1137/16M1073121 

Cornell Universiry Library published a paper by faculty member Matthew J. Hirn on 15 August, 2016.

Link: https://arxiv.org/abs/1608.03628

CMSE researchers Gautham Dharuman & Michael Murillo have a new paper published by The Journal of Chemical Physics for their work involving Ewald method and medium-range interactions for charged-particle systems.

Link: http://dx.doi.org/10.1063/1.4973842

CMSE Faculty Jose Perea's paper was published by The Cornell University Library for his work in Topology submitted on 26 April 2017.

Link: https://arxiv.org/abs/1704.08382

Multiscale Modeling and Simulation has published the following paper by Matthew Hirn, Stephane Mallat, & Nicolas Poilvert for their work in Wavelet Scattering on 2 May 2017.

Link: http://epubs.siam.org/doi/abs/10.1137/16M1075454

CMSE Professor Mohsen Zayernouri, the director of FMATH group, published a new paper in SIAM Journal of Scientific Computing (SIAM J. Sci. Comput., 39(3), A922–A946) on 25 May 2017. 

Link: http://epubs.siam.org/doi/abs/10.1137/17M1113060

The Biophysical Journal had published a paper by Alex Dickson & Samual D. Lotz, published on 28 February 2017 for their work on Ligand Pathways.

Link: http://www.sciencedirect.com/science/article/pii/S0006349517300450

Current Topics in Medicinal Chemistry featured a new paper by Alex Dickson, Pratyush Tiwary, & Harish Vashisth on 14 April 2017 for their work in Kinetics of Ligand Binding.

Link: https://www.ncbi.nlm.nih.gov/pubmed/28413946

The Journal of Computational Chemistry featured a new paper by Alex Dickson, Christopher T. Bailey, & John Karanicolas, on 5 June 2017.

Link: http://onlinelibrary.wiley.com/doi/10.1002/jcc.24517/full

CMSE Professor Mohsen Zayernouri, the director of FMATH group, has published a new paper in The Journal of Chaos, Solitons, & Fractals (2017).

Link: https://doi.org/10.1016/j.chaos.2017.03.051

Xianfeng Hu, Mark Iwen, & Hyejin Kim authored a new paper for their work in Rapid Computing published by Numer. Algor. (2017) 74: 1029.
DOI: 10.1007/s11075-016-0184-x

Link: http://users.math.msu.edu/users/markiwen/Papers/Legendre_SUBMITTED.pdf

Ariel Herbert-Voss, Matthew J. Hirn, & Frederick McCollum published a paper in Revista Mathematica Iberoamericana for their work on Computing Minimal Interpolants.

Link: http://www.ems-ph.org/journals/show_abstract.php?issn=0213-2230&vol=33&iss=1&rank=2

The Murillo Group has released a new paper published by Physical Review E on April 10th, 2017 about Hydrogen Plasmas within the Coupled-mode Regime.

Link: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.95.043202

M. S. Murillo & M. Marciante published a new paper on Thermodynamic and Kinetic Properties in Phys. Rev. Lett. 118, 025001 – 10 January 2017
Link: https://doi.org/10.1103/PhysRevLett.118.025001
 

M. Zayernouri & G.E. Karniadakis published a new paper in The Journal of Computational Physics, vol. 257, Part A, pp. 460–480, Jan. 2014.
DOI: 10.1016/j.jcp.2013.09.039
Link: http://www.sciencedirect.com/science/article/pii/S0021999113006530

CMSE Professor Mohsen Zayernouri, the director of FMATH group, has published a new paper in Computer Methods in Applied Mechanics and Engineering.

Link: doi:10.1016/j.cma.2016.05.030