Ted Baltz Skip to main content Explore our many areas of focus Explore all research areas Applied AI & sciences Earth AI Health AI Science AI Sustainability & crisis resilience Foundational ML & algorithms Algorithms & theory Information retrieval Machine intelligence Machine perception Natural language processing People, systems & quantum AI Human-computer interaction and visualization Networking Quantum AI Responsible AI Anti abuse Software engineering Software systems Learn More Publications Projects Building a collaborative ecosystem Datasets Access high-quality datasets to accelerate your research. Tools & services Explore our latest AI models and products. Open source Discover open-source code and collaborate with the community. Shaping the future together See all programs Faculty programs Participating in the academic research community through meaningful engagement with university faculty. 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Google Research Google AI Learn about all our AI Google DeepMind Explore the frontier of AI Google Labs Try our AI experiments Research Resources Conferences & events Careers Blog About Search Home People Ted Baltz Research Areas Machine intelligence Authored Publications See Filters results Filter by: Clear Publications Google 8 Other 0 Years 2021 2 2020 1 2019 2 2018 2 2017 1 Research Areas Algorithms and Theory 1 Data Mining and Modeling 1 General Science 7 Health & Bioscience 1 Teams Applied science 6 Climate and Sustainability 1 Sort By Title Title, descending Year Year, descending chip template Remove Multi-instrument Bayesian reconstruction of plasma shape evolution in C-2W experiment Anton Kast Erik Trask Hiroshi Gota Ian Langmore Jesus Romero John Platt Michael Dikovsky Peter Norgaard Rob von Behren Scott Davidson Geraedts Ted Baltz Tom Madams Physics of Plasmas (2021) Preview Preview abstract We determined the time-dependent geometry including high-frequency oscillations of the plasma density in TAE’s C2W experiment. This was done as a joint Bayesian reconstruction from a 14-chord FIR interferometer in the midplane, 32 Mirnov probes at the periphery, and 8 shine-through detectors at the targets of the neutral beams. For each point in time we recovered, with credibility intervals: the radial density profile of the plasma; bulk plasma displacement; amplitudes, frequencies and phases of the azimuthal modes n=1 to n=4. Also reconstructed were the radial profiles of the deformations associated with each of the azimuthal modes. Bayesian posterior sampling was done via Hamiltonian Monte Carlo with custom preconditioning. This gave us a comprehensive uncertainty quantification of the reconstructed values, including correlations and some understanding of multimodal posteriors. This method was applied to thousands of experimental shots on C-2W, producing a rich data set for analysis of plasma performance. View details OVERVIEW OF C-2W: HIGH TEMPERATURE, STEADY-STATE BEAM-DRIVEN FIELD-REVERSED CONFIGURATION PLASMAS Anton Kast Ian Langmore John Platt Michael Dikovsky Peter Norgaard Rob von Behren Scott Davidson Geraedts TAE Ted Baltz Tom Madams William D Heavlin Nuclear Fusion (2021) Preview Preview abstract TAE Technologies, Inc. (TAE) is pursuing an alternative approach to magnetically confined fusion, which relies on field-reversed configuration (FRC) plasmas composed of mostly energetic and well-confined particles by means of a state-of-the-art tunable energy neutral-beam (NB) injector system. TAE’s current experimental device, C-2W (also called “Norman”), is the world’s largest compact-toroid device and has made significant progress in FRC performance, producing record breaking, high temperature (electron temperature, Te 500 eV; total electron and ion temperature, Ttot 3 keV) advanced beam-driven FRC plasmas, dominated by injected fast particles and sustained in steady-state for up to 30 ms, which is limited by NB pulse duration. C-2W produces significantly better FRC performance than the preceding C-2U experiment, in part due to Google’s machine-learning framework for experimental optimization, which has contributed to the discovery of a new operational regime where novel settings for the formation sections yield consistently reproducible, hot, and stable plasmas. Active plasma control system has been developed and utilized in C-2W to produce consistent FRC performance as well as for reliable machine operations using magnets, electrodes, gas injection, and tunable NBs. The active control system has demonstrated a stabilization of FRC axial instability. Overall FRC performance is well correlated with NBs and edge-biasing system, where higher total plasma energy is obtained with increasing both NB injection power and applied-voltage on biasing electrodes. C-2W divertors have demonstrated a good electron heat confinement on open-field-lines using strong magnetic mirror fields as well as expanding the magnetic field in the divertors (expansion ratio 30); the electron energy lost per ion, ~6–8, is achieved, which is close to the ideal theoretical minimum. View details Learning causal networks using inducible transcription factors and transcriptome‐wide time series Marc Berndl Marc Coram Minjie Fan R. Scott McIsaac Sean Hackett Ted Baltz (2020) Preview Preview abstract We present IDEA (the Induction Dynamics gene Expression Atlas), a dataset constructed by independently inducing hundreds of transcription factors (TFs) and measuring timecourses of the resulting gene expression responses in budding yeast. Each experiment captures a regulatory cascade connecting a single induced regulator to the genes it causally regulates. We discuss the regulatory cascade of a single TF, Aft1, in detail; however, IDEA contains 200 TF induction experiments with 20 million individual observations and 100,000 signal‐containing dynamic responses. As an application of IDEA, we integrate all timecourses into a whole‐cell transcriptional model, which is used to predict and validate multiple new and underappreciated transcriptional regulators. We also find that the magnitudes of coefficients in this model are predictive of genetic interaction profile similarities. In addition to being a resource for exploring regulatory connectivity between TFs and their target genes, our modeling approach shows that combining rapid perturbations of individual genes with genome‐scale time‐series measurements is an effective strategy for elucidating gene regulatory networks. View details Formation of Hot, Stable, Long-Lived Field-Reversed Configuration Plasmas on the C-2W Device The TAE Team Ted Baltz John Platt Nuclear Fusion, 59 (2019), pp. 112009 Preview Preview abstract TAE Technologies’ research is devoted to producing high temperature, stable, long-lived field-reversed configuration (FRC) plasmas by neutral-beam injection (NBI) and edge biasing/control. The newly constructed C-2W experimental device (also called “Norman”) is the world’s largest compact-toroid (CT) device, which has several key upgrades from the preceding C-2U device such as higher input power and longer pulse duration of the NBI system as well as installation of inner divertors with upgraded electrode biasing systems. Initial C-2W experiments have successfully demonstrated a robust FRC formation and its translation into the confinement vessel through the newly installed inner divertor with adequate guide magnetic field. They also produced dramatically improved initial FRC states with higher plasma temperatures (Te ~250+ eV; total electron and ion temperature 1.5 keV, based on pressure balance) and more trapped flux (up to ~15 mWb, based on rigid-rotor model) inside the FRC immediately after the merger of collided two CTs in the confinement section. As for effective edge control on FRC stabilization, a number of edge biasing schemes have been tried via open field-lines, in which concentric electrodes located in both inner and outer divertors as well as end-on plasma guns are electrically biased independently. As a result of effective outer-divertor electrode biasing alone, FRC plasma is well stabilized and diamagnetism duration has reached up to ~9 ms which is equivalent to C-2U plasma duration. Magnetic field flaring/expansion in both inner and outer divertors plays an important role in creating a thermal insulation on open field-lines to reduce a loss rate of electrons, which leads to improvement of the edge and core FRC confinement properties. Experimental campaign with inner-divertor magnetic-field flaring has just commenced and early result indicates that electron temperature of the merged FRC stays relatively high and increases for a short period of time, presumably by NBI and ExB heating. View details Fusion Plasma Reconstruction Ian Langmore John Platt Michael Dikovsky Nathan Neibauer Peter Norgaard Rob von Behren Scott Davidson Geraedts Ted Baltz (2019) Preview Preview abstract Fusion Plasma Reconstruction work done at Google in partnership with TAE is presented. View details Application of Bayesian inference for reconstruction of FRC plasma state in C-2W Erik Trask Hiroshi Gota Ian Langmore Jesus Romero Matthew Thompson Michael Dikovsky Peter Norgaard Ted Baltz Tom Madams Yair Carmon (2018) Preview Preview abstract Bayesian methods are used to infer Field Reversed Configuration (FRC) plasma properties for the C-2W machine at TAE Technologies. The approach starts with a statistical distribution of possible plasma states, where physically-motivated constraints are imposed through the Bayesian prior. Possible states are processed by a forward model for the relevant instruments to assess agreement with corresponding measured experimental data. The resulting probability distribution is known as the posterior, from which the most likely plasma state and the corresponding statistical confidence are extracted. Plasma state reconstruction from multi-instrument Bayesian inference are presented in this study, implemented for the upgraded diagnostics that have come online for C-2W. FIR interferometry, Thomson scattering, Bremsstrahlung radiation measurement, and secondary electron emission detection from the neutral beams are used in reconstruction near the FRC midplane. Magnetic probes and imaging from a high-speed camera provide 3D data throughout the main confinement vessel. This study aims to further the understanding of plasma properties and dynamics, such as electron and ion densities, electron temperature, plasma current, and magnetic field topology. View details The Plasma Debugger Erik Granstedt Erik Trask Hiroshi Gota Ian Langmore Jesus Romero Matthew Thompson Michael Dikovsky Peter Norgaard Roberto Mendoza Ted Baltz Tom Madams Yair Carmon (2018) Preview Preview abstract We built a "Plasma Debugger", a tool to reconstruct the state of the FRC plasma in the TAE Technologies' experimental machine C­2W. This generalized Bayesian inference approach combines data from magnetic sensors, fast cameras, FIR interferometer, Thomson Scattering system, Bremsstrahlung measurements and neutral beams shine­-through SEE detectors. It then reconstructs electron density, temperature and bulk plasma currents, with confidence intervals. Computation takes hundreds of CPUs and is performed in the cloud, with results showing up in the plasma machine control room within several minutes of the experiment. The display shows time evolution of the basic plasma properties, giving machine operators additional insight into the plasma behavior. View details Achievement of Sustained Net Plasma Heating in a Fusion Experiment with the Optometrist Algorithm E.A. Baltz E. Trask M. Binderbauer M. Dikovsky H. Gota R. Mendoza J.C. Platt P.F. Riley Scientific Reports, 7 (2017), pp. 6425 Preview Preview abstract Many fields of basic and applied science require efficiently exploring complex systems with high dimensionality. An example of such a challenge is optimising the performance of plasma fusion experiments. The highly-nonlinear and temporally-varying interaction between the plasma, its environment and external controls presents a considerable complexity in these experiments. A further difficulty arises from the fact that there is no single objective metric that fully captures both plasma quality and equipment constraints. To efficiently optimise the system, we develop the Optometrist Algorithm, a stochastic perturbation method combined with human choice. Analogous to getting an eyeglass prescription, the Optometrist Algorithm confronts a human operator with two alternative experimental settings and associated outcomes. A human operator then chooses which experiment produces subjectively better results. This innovative technique led to the discovery of an unexpected record confinement regime with positive net heating power in a field-reversed configuration plasma, characterised by a 50% reduction in the energy loss rate and concomitant increase in ion temperature and total plasma energy. View details Search on Google Scholar Join us We're always looking for more talented, passionate people. 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