Eve Armstrong

New York Institute of Technology

Research Associate, Department of Astrophysics

Research Interests

Themes

  • Nonlinear models in astrophysics: neutrino flavor evolution and exoplanet atmospheres.
  • Nonlinear models in neuroscience: biological neuronal networks associated with audition.
  • The information content of time series signals: in astrophysics, neuroscience, and acoustic communication.
  • Pattern generation and recognition.

Approaches

  • Dynamical systems; optimization-based inference procedures based in statistical physics.

I am a dynamicist who is perplexed by the behavior of space, time, sound, and brains. I am an assistant professor in the Department of Physics at New York Institute of Technology in Manhattan, and research associate in the Department of Astrophysics at AMNH. Within astrophysics, I work on nonlinear dynamical models of processes that give rise to observable quantities, and methods of statistical data assimilation—an inference procedure designed to optimize a model with observation—to yield insight into such problems.  

Recently I began collaborating with the exoplanet research group of Jackie Faherty at AMNH, aiming to infer atmospheric chemical composition of exoplanets given an observed flux of light across wavelengths. A separate and ongoing collaboration involves a global network of theoretical astrophysicists seeking to infer neutrino flavor evolution following supernova core-collapse events, based on an observed neutrino energy flux arriving at an Earth-based detector.  Our first publication is here, and current collaborators are: George Fuller, Amol Patwardhan, Baha Balentekin, Chad Kishimoto, Shashank Shalgar, and Mark Paris

In addition, I develop theatrical methods for public engagement with science and write science humor.

Website

http://reality-aside.com/research/

Publications

 Articles in preparation

  1. Armstrong, E., Zeng, A., Perkes, A., Anderson, L., Schmidt, M.  Toward dynamical systems representation of birdsong to predict song preferences in female cowbirds.
  2. Zeng, A., Armstrong, E., Balasubramanian, V., Perkes, A., Anderson, L., Balasubramanian, V., Schmidt, M.  A nonlinear dynamics representation of cowbird song.

In-press articles

  1. Armstrong, E.  Statistical data assimilation for estimating electrophysiology simultaneously with connectivity within a biological neuronal network  (Accepted: Phys. Rev. E); arXiv preprint https://arxiv.org/abs/ 1711.03834, 2020

Published scientific articles

  1. Armstrong, E., Patwardhan, A.V., Johns, L., Kishimoto, C.T., Abarbanel, H.D.I., Fuller, G.M.  A Path-integral-based Approach to Neutrino Flavor Evolution.  Physical Review D 96(8): 083008, 2017
  2. Abarbanel, H.D.I., Shirman, S., Breen, D., Kadakia, N., Rey, D., Armstrong, E., Margoliash, D.  A Unifying View of Synchronization for Data Assimilation in Complex Nonlinear Networks.  Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(12): 126802, 2017
  3. Abarbanel, H.D.I., Shirman, S., Armstrong, E., Dean D., Extracellular Potentials as Data Assimilation Measurement Functions for the Dynamics in Networks of Neurons.  (In preparation)
  4. Armstrong, E., Abarbanel, H.D.I.  Model of the songbird nucleus HVC as a network of central pattern generators, J. Neurophysiol. 116(5): 2405-2419, 2016
  5. Kadakia, N., Armstrong, E., Breen, D., Morone, U., Daou, A., Margoliash, D., Abarbanel, H. D.I.,  Nonlinear Statistical Data Assimilation for HVCRA Neurons in the Avian Song System. Biological Cybernetics 110.6:417-434, 2016
  6. Breen, D., Shirman, S., Armstrong, E., Daou, A., Margoliash, D., Abarbanel, H.D.I.  HVC Interneuron Properties from Statistical Data Assimilation.  arXiv preprint arXiv: 1608:04433, 2016
  7. Armstrong, E., Patterson, J., Michelsen, E., Thorstensen, J., Uthas, H., Vanmunster, T., Hambsch, F.-J., Roberts, G., Dvorak, S., Orbital, Superhump, and Superorbital Periods in the Cataclysmic Variables AQ Mensae and IM Eridani.  Monthly Notices of the Royal Astronomical Society (MNRAS) 435, 707, 2013
  8. Armstrong, E., Patterson, J., Kemp, J.  Two Photometric Periods in the AM CVn System CP Eridani.   MNRAS 421, 2310, 2012
  9. Skinner, J., Thorstensen, J., Armstrong, E., Brady, S.  The New Eclipsing Cataclysmic Variable SDSS 154453+255.  Publications of the Astron. Soc. of the Pacific (PASP) 123, 901, 2011
  10. Copperwheat, C.M., Marsh, T., Dhillon, V., Littlefair, S., Woudt, A., Warner, B., Patterson, J., Steeghs, D., Kemp, J., Armstrong, E., Rea, R.  The Photometric Period in ES Ceti.  MNRAS 413, 3068, 2011
  11. Dai, X, Halpern, J., Morgan, N., Armstrong, E., Mirabal, N., Haislip, J., Reichart, D., Stanek, K., Optical and X-Ray Observations of GRB 060526: A Complex Afterglow Consistent with an Achromatic Jet Break.  Astrophysical Journal (Ap J) 658, 509, 2007
  12. Armstrong, E. et. al. GRB 060102: MDM Observation, GRB Coordinates Network, Circular Service 4427, 1, 2006
  13. Thorstensen, J., Armstrong, E.  Is FIRST J102347.6+003841 Really a Cataclysmic Binary?   Astronomical Journal (AJ) 130, 759, 2005
  14. Patterson, J., Thorstensen, J., Armstrong, E.  The Dwarf Nova PQ Andromedae.  PASP 117, 922, 2005
  15. Patterson, J. and 19 co-authors, Superhumps in Cataclysmic Binaries. XXV. qcrit, epsilon(q), and Mass-Radius.  PASP 117, 1204, 2005
  16. Patterson, J., Thorstensen, J., Vanmunster, T., Fried, R., Martin, B., Campbell, T., Robertson, J., Kemp, J., Messier, D., Armstrong, E., Rapid Oscillations in Cataclysmic Variables. XVI. DW Cancri.  PASP 116, 516, 2004
  17. Pretorius, M.L. Woudt, P., Warner, B., Bolt, G., Patterson, J., Armstrong, E., High-speed photometry of SDSS J013701.06 - 091234.9.  MNRAS 352, 1056, 2004
  18. Mirabal, N. Halpern, J., Chornock, R., Filippenko, A., Terndrup, D., Armstrong, E., Kemp, J., Thorstensen, J., Tavarez, M., Espaillat, C., GRB 021004: A Possible Shell Nebula around a Wolf-Rayet Star Gamma-Ray Burst Progenitor.  Ap J 595, 935, 2003

Articles of questionable scientific value

  1. Armstrong, E. Colonel Mustard in the Aviary with the Candlestick: a limit cycle attractor transitions to a stable focus via supercritical Andronov-Hopf bifurcation.  https://arxiv.org/abs/1803.11559
  2. Armstrong, E.  A Neural Networks Approach to Predicting How Things Might Have Turned Out Had I Mustered the Nerve to Ask Barry Cottonfield to the Junior Prom Back in 1997.  arXiv preprint arXiv:1703:10449, 2017 April 1
  3. Armstrong, E. Pipe-cleaner Model of Neuronal Network Dynamics.  arXiv preprint arXiv:1603:09723, 2016 April 1
  4. Armstrong, E.  Non-detection of the Tooth Fairy at Optical Wavelengths.  arXiv preprint arXiv:1204.0492 2012 April 1; Journal of Irreproducible Results 52, 3: 22-25, 2014

Educational material

Developed a textbook for Columbia College course “Frontiers of Science” (2004), which is a core requirement for undergraduates (as of 2005). Full text: http://ccnmtl.columbia.edu/projects/mmt/frontiers/index.html