Staff information

PNNL Publications

2023

• Ashtari Esfahani A., S. Boser, N.G. Buzinsky, M.C. Carmona-Benitez, C. Claessens, L. De Viveiros, and P.J. Doe, et al. 2023. "Tritium Beta Spectrum Measurement and Neutrino Mass Limit from Cyclotron Radiation Emission Spectroscopy." Physical Review Letters 131, no. 10:Art. No. 102502. PNNL-SA-180658. doi:10.1103/PhysRevLett.131.102502

2022

• Ashtari Esfahani A., Z. Bogorad, S. Boser, N.G. Buzinsky, C. Claessens, L. De Viveiros, and M. Fertl, et al. 2022. "Viterbi Decoding of CRES Signals in Project 8." New Journal of Physics 24, no. 5:Art. No. 053013. PNNL-SA-169354. doi:10.1088/1367-2630/ac66f6

2021

• Alexander F.J., J.A. Ang, J.A. Bilbrey, J. Balewski, T.A. Casey, R. Chard, and J. Choi, et al. 2021. "Co-design Center for Exascale Machine Learning Technologies (ExaLearn)." The International Journal of High Performance Computing Applications 35, no. 6:598-616. PNNL-SA-156070. doi:10.1177/10943420211029302
• Bedaque P., A. Boehnlein, M. Cromaz, M. Diefenthaler, L. Elouadrhiri, T. Horn, and M. Kuchera, et al. 2021. "A.I. for nuclear physics." European Physical Journal. A, Hadrons and nuclei. 57, no. 3:Article No. 100. PNNL-SA-160859. doi:10.1140/epja/s10050-020-00290-x
• St. John J., C. Herwig, D. Kafkes, J. Mitrevski, W. Pellico, G. Perdue, and A. Quintero-Parra, et al. 2021. "Real-time Artificial Intelligence for Accelerator Control: A Study at the Fermilab Booster." Physical Review Accelerators and Beams 24, no. 10:Article No. 104601. PNNL-SA-157642. doi:10.1103/PhysRevAccelBeams.24.104601
• Strube J.F., M. Schram, S. Rustam, Z.C. Kennedy, and T. Varga. 2021. "Identifying build orientation of 3D-printed materials using convolutional neural networks." Statistical Analysis and Data Mining 14, no. 6:575-582. PNNL-SA-153051. doi:10.1002/sam.11497

2020

• Ashtari Esfahani A., S. Boser, N.G. Buzinsky, R. Cervantes, C. Claessens, L. De Viveiros, and M. Fertl, et al. 2020. "Cyclotron Radiation Emission Spectroscopy Signal Classification with machine Learning in Project 8." New Journal of Physics 22, no. 3:Article No. 033004. PNNL-SA-146046. doi:10.1088/1367-2630/ab71bd
• Bilbrey J.A., C.M. Ortiz Marrero, M. Sassi, A.M. Ritzmann, N.J. Henson, and M. Schram. 2020. "Tracking the chemical evolution of iodine species using recurrent neural networks." ACS Omega 5, no. 9:4588-4594. PNNL-SA-148824. doi:10.1021/acsomega.9b04104
• Bilbrey J.A., J. Heindel, M. Schram, P. Bandyopadhyay, S.S. Xantheas, and S. Choudhury. 2020. "A Look Inside the Black Box: Using graph-theoretical descriptors to interpret a Continuous-Filter Convolutional Neural Network (CF-CNN) trained on the global and local minimum energy structures of neutral water clusters." Journal of Chemical Physics 153, no. 2:024302. PNNL-SA-152462. doi:10.1063/5.0009933
• Schram M., M. Thomas, K.M. Fox, B.H. LaRoque, B.A. VanDevender, N.S. Solomon-Oblath, and D.E. Cowley. 2020. "Distributed Computing for the Project 8 Experiment." In 24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019). EPJ Web Conference, 245, Paper No. 03030. Paris:EDP Sciences. PNNL-SA-158419. doi:10.1051/epjconf/202024503030
• Thomas M., M. Schram, K.M. Fox, J.F. Strube, N.S. Solomon-Oblath, R.J. Rallo Moya, and Z.C. Kennedy, et al. 2020. "Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems." MRS Advances 5, no. 29-30:1547-1555. PNNL-SA-150139. doi:10.1557/adv.2020.103
• Thomas M., M. Schram, K.M. Fox, J.F. Strube, N.S. Solomon-Oblath, R.J. Rallo Moya, and Z.C. Kennedy, et al. 2020. "Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems." MRS Advances 5, no. 29-30:1547-1555. PNNL-SA-147390. doi:10.1557/adv.2020.103

2019

• Ashtari Esfahani A., S. Boser, N.G. Buzinsky, R. Cervantes, C. Claessens, L. De Viveiros, and M. Fertl, et al. 2019. "Locust: C++ software for simulation of RF detection." New Journal of Physics 21, no. 11:Article No. 113051. PNNL-SA-145576. doi:10.1088/1367-2630/ab550d
• Ashtari Esfahani A., V. Bansal, S. Boser, N.G. Buzinsky, R. Cervantes, C. Claessens, and L. de Viveiros, et al. 2019. "Electron Radiated Power in Cyclotron Radiation Emission Spectroscopy Experiments." Physical Review C 99, no. 5:Article No. 055501. PNNL-SA-140989. doi:10.1103/PhysRevC.99.055501
• Schram M., N.R. Tallent, R.D. Friese, A. Singh, and I. Altintas. 2019. "Application of Deep Learning on Integrating Prediction, Provenance, and Optimization." In Proceedings of the 23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018), EPJ Web of Conferences, 214, Article No. 06007. PNNL-SA-147454. doi:10.1051/epjconf/201921406007
• Strube J.F., K. Bhattacharya, E.D. Church, J.A. Daily, M. Schram, C.M. Siegel, and K.J. Wierman. 2019. "Scaling studies for deep learning in Liquid Argon Time Projection Chamber event classification." In 23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018), July 9-13, 2018, Sofia, Bulgaria. EPJ Web of Conferences, 214, Paper No. 06016. PNNL-SA-139482. doi:10.1051/epjconf/201921406016
• Suetterlein J.D., R.D. Friese, N.R. Tallent, and M. Schram. 2019. "TAZeR: Hiding the Cost of Remote I/O in Distributed Scientific Workflows." In IEEE International Conference on Big Data (Big Data 2019), December 9-12, 2019, Los Angeles, CA, 383-394. Piscataway, New Jersey:IEEE. PNNL-SA-148879. doi:10.1109/BigData47090.2019.9006418

2018

• Ritter M., L.S. Wood, T. Kuhr, M. Bracko, T.O. Elsethagen, K.M. Fox, and J.C. Hall, et al. 2018. "Belle II Conditions Database." Journal of Physics: Conference Series 1085, no. 3:Article No. 032032. PNNL-SA-130199. doi:10.1088/1742-6596/1085/3/032032
• Singh A., I. Altintas, M. Schram, and N.R. Tallent. 2018. "Deep Learning for Enhancing Fault Tolerant Capabilities of Scientific Workflows." In Proceedings of the IEEE International Conference on Big Data, (Big Data 2018), December 10-13, 2018, Seattle, WA, edited by Y. Song, et al, 3905-3914, Article No. 8622509. Piscataway, New Jersey:IEEE. PNNL-SA-143406. doi:10.1109/BigData.2018.8622509

2017

• Schram M., V. Bansal, R.D. Friese, N.R. Tallent, J. Yin, K.J. Barker, and E.G. Stephan, et al. 2017. "Integrating prediction, provenance, and optimization into high energy workflows." Journal of Physics: Conference Series 898, no. 6:Article No. 062052. PNNL-SA-129007. doi:10.1088/1742-6596/898/6/062052
• Singh A., E.G. Stephan, M. Schram, and I. Altintas. 2017. "Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows." In IEEE 13th International Conference on e-Science (e-Science 2017), October 24-27, 2017, Auckland, New Zealand, 586-591. Los Alamitos, California:IEEE Computer Society. PNNL-SA-136096. doi:10.1109/eScience.2017.94

2016

• Elsethagen T.O., E.G. Stephan, B. Raju, M. Schram, M.C. Macduff, D.J. Kerbyson, and K. Kleese-Van Dam, et al. 2016. "Data Provenance Hybridization Supporting Extreme-Scale Scientific WorkflowApplications." In New York Scientific Data Summit (NYSDS 2016), August 14-17, 2016, New York. Piscataway, New Jersey:IEEE. PNNL-SA-119959. doi:10.1109/NYSDS.2016.7747819

2015

• Asner D.M., K.A. Burns, L.W. Campbell, B.A. Greenfield, M.S. Kos, J.L. Orrell, and M. Schram, et al. 2015. "Method of Fission Product Beta Spectra Measurements for Predicting Reactor Anti-neutrino Emission." Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment 776. PNNL-SA-101212. doi:10.1016/j.nima.2014.09.076
• Kronenbitter B., M. Heck, P. Goldenzweig, T. Kuhr, A. Abdesselam, I. Adachi, and H. Aihara, et al. 2015. "Measurement of the branching fraction of B+ ? t+?t decays with the semileptonictagging method." Physical Review D 92, no. 5:Article No. 051102(R). PNNL-SA-112069. doi:10.1103/PhysRevD.92.051102

2013

• Asner D.M., K.A. Burns, B.A. Greenfield, M.S. Kos, J.L. Orrell, M. Schram, and B.A. VanDevender, et al. 2013. "Predicting Reactor Antineutrino Emissions Using New Precision Beta Spectroscopy." In The Snowmass 2013 Proceedings: Planning the Future of US Particle Physics, July 29-August 6, 2013, Minneapolis, Minnesota. Menlo Park:Snowmass Electronic Proceedings. PNNL-SA-94947.