Recent Publications

Validation of first-principles turbulence simulation in diverted negative triangularity plasmas on DIII-D

Philipp Ulbl, Alessandro Marinoni, Baptiste J. Frei, Filippo Scotti, Samuel D. Stewart, Gabriele Merlo, Frank Jenko, Kathreen E. Thome

We present a first-principles gyrokinetic simulation of the edge and scrape-off layer (SOL) region of negative triangularity (NT) plasmas in the DIII-D tokamak, achieving remarkable agreement with experimental data for density, ion temperature, and electron temperature profiles. Notably, our simulation validates edge and SOL ion temperature profiles in electrostatic turbulence dominated conditions for the first time. The NT edge region is found to be dominated by trapped electron modes, with a transition toward ion temperature gradient-like modes at the outer edge. The SOL heat fluxes on divertor targets exhibit an Eich profile shape, consistent with experimental observations, with a similar but slightly narrower width than measured experimentally. The simulation demonstrates the presence of geodesic acoustic modes, and our analysis reveals the characteristics of their interaction with turbulent fluctuations. This successful validation marks a significant step toward self-consistent predictions of turbulence, edge profiles, and heat exhaust in future fusion devices.

IGNITE Tokamak World Model Architecture

Peter Steiner, Azarakhsh Jalalvand, Nathaniel Chen, Kouroche Bouchiat, Ricardo Shousha, SangKyeun Kim, Egemen Kolemen

We introduce IGNITE, a generative world foundation model for fusion plasma behavior simulation trained in a self-supervised manner from over a decade of unlabeled experimental data at the DIII-D National Fusion Facility. The core of IGNITE is a dynamics model that can simulate DIII-D discharges from a given set of actuator trajectories. These trajectories can be supplied or generated on-the-fly from a textual prompt or from desired experimental outcomes. The model architecture consists of several spatio-temporal tokenizers that embed the different input modalities, including time-series like spatio-temporal measurement data, image sequences, and high-resolution spectrograms, each of which collected at vastly different time scales. The backbone is composed of an auto-regressive dynamics model that has the capacity to predict entire DIII-D discharges given initial latent plasma states and actuator trajectories over a theoretical infinite horizon. IGNITE paves the way towards efficient AI-driven experimental planning and world modeling for nuclear fusion.

Is Your AI Fast Enough to Run a Fusion Reactor?

Nathaniel Chen, Andrew Rothstein, Ricardo Shousha, Hiro Farre-Kaga, Peter Steiner, Azarakhsh Jalalvand, Egemen Kolemen

Machine learning models are increasingly used in feedback control loops for nuclear fusion, where inference speed and predictable timing are critical. We summarize lessons from models deployed for control on the DIII-D tokamak and develop a benchmark to compare inference backends across ten neural networks and model components from fusion control and diagnostic pipelines. For models greater than five million parameters, the CPU backends take tens to thousands of milliseconds, while GPU inference is substantially faster, suggesting an upper limit on CPU-oriented development for control. These results show why the deployment backend must be selected together with the model and its control-cycle budget.

Transport Impacts of Resonant Island Chains in Fusion Plasmas

Sidney D. V. Williams, Kevin Mitchell, Ethan Custodio, Dmitri M. Orlov

Magnetic field-line transport in magnetically confined plasmas is commonly modeled as diffusion through stochastic magnetic layers generated by resonant perturbations. However, experimentally relevant magnetic configurations frequently exhibit transport rates that are substantially slower than predicted by fully stochastic models, indicating the presence of unresolved dynamical barriers. In this work, we investigate the role of nested resonant island chains and their associated invariant manifolds in regulating transport within the edge magnetic topology of DIII-D tokamak discharge #171491 subjected to strong n=3 resonant magnetic perturbations. Using field-line tracing, Poincare analysis, and manifold calculations, we identify a hierarchy of homoclinic and heteroclinic tangles associated with both period-one and period-ten hyperbolic points. A systematic construction based on primary intersection points is developed to extract partial transport barriers from the full manifold geometry and divide the chaotic region into dynamically distinct domains. Monte Carlo simulations reveal that field-line escape exhibits a bi-exponential character when only the outermost period-one boundary is considered, reflecting the presence of a long-lived "sticky" region associated with the period-ten island chain. When the inner period-ten boundary is explicitly incorporated into the Monte Carlo, the escape process becomes approximately single exponential and is accurately described by turnstile lobe transport. The measured escape rate agrees with predictions obtained from the turnstile lobe area and the symplectic structure of the field-line map. These results demonstrate that nested tangles provide a quantitative transport skeleton governing magnetic-field-line escape and establish a framework for analyzing transport barriers, cantori, and lobe dynamics in realistic fusion-plasma magnetic configurations.

Phase space resolved measurements of fast-ion density fluctuations and energy transfer induced by Alfvén eigenmodes

Jose Rueda-Rueda, Xiaodi Du, William W Heidbrink, Gregory G Howes, Pablo Oyola, Tommaso Barberis, Deyong Liu, Michael A Van Zeeland, Filipp Khabanov, Kyle Callahan

We present phase-space resolved measurements of energetic particle (EP) fluctuations near Toroidal Alfvén Eigenmode (TAE) frequencies in the DIII-D tokamak. A newly rebuilt fast channel in the Imaging Neutral Particle Analyzer (INPA) system, with a significantly improved signal-to-noise ratio, enabled the detection of fluctuations at approximately 100-130 kHz, frequencies that were previously inaccessible. Coherent fluctuations with amplitudes of about 1\% were observed in localized regions of EP phase space. The secular energy exchange rate between the wave and the EP population is directly extracted from the observed INPA and electron density and temperature fluctuations, accounting for both parallel and perpendicular electric field components. Analysis reveals that poloidal energy exchange dominates by approximately two orders of magnitude over parallel and radial components, with energy transfer occurring through the interaction between drift velocities and perpendicular electric fields. The averaged energy exchange rates are of the order of 10 keV/s. A comparison with ASCOT orbit-following simulations confirms that the observed fluctuations originate from the passively viewed (trapped) particle population rather than from passing particles. The measured TAE radial structure shows good agreement with ideal MHD simulations using the NOVA code. These measurements provide unprecedented experimental validation of wave-particle energy transfer mechanisms.

Forecasting the first edge localized mode (ELM) after LH-transition with a neural network trained on Doppler Backscattering data from DIII-D

Nathan Qi Xuan Teo, Kshitish Kumar Barada, Valerian Hongjie Hall-Chen, Lin Gu, Terry L Rhodes

In H-mode tokamak and stellarator plasmas, edge localized modes (ELMs) lead to the expulsion of heat and particles beyond the edge transport barrier. ELMs cause a loss of energy and have the potential to damage the divertor and other plasma facing components, which motivates efforts to forecast such events to work alongside mitigation systems. In this paper, we use the Doppler backscattering (DBS) diagnostic data as input to train a neural network model, adapted from DeepHit [Lee et al., Deephit, AAAI 2018], to forecast the first ELM crash of H-mode discharges in DIII-D. The model takes 50 ms of DBS spectrogram data and predicts the probability of an ELM crash occurring within set time windows. Training and testing on shots found in the DIII-D database, we find the initial results promising, with the model reliably forecasting the first ELM 100 ms before it occurs. This successful proof-of-concept lays a strong foundation for a predictive tool that can deploy ELM-mitigation techniques before an ELM crash occurs. Future work will expand the training set with carefully selected shots and refine the neural network architecture to improve model robustness to noise and data variation.

Horizon-Aware Early Event Prediction for Tokamak Disruption Alarms

Takeshi Koshizuka, Takaharu Yaguchi

Reliable disruption prediction is essential for the safe operation of future tokamaks. Existing full-distribution survival methods model the complete residual time-to-disruption distribution, whereas operational decisions primarily depend on disruption risk within a finite prediction horizon. This mismatch motivates introducing Early Event Prediction (EEP) objectives into survival-based disruption prediction. We take Deep Survival Machines (DSM) as the full-distribution baseline and propose applying two established EEP methods to tokamak disruption prediction: Temporal Label Smoothing (TLS), which directly predicts disruption probability within a finite horizon, and survTLS, which additionally models the event-time distribution within that horizon. Using a common causal encoder, we compare these methods on DIII-D, Alcator C-Mod, and EAST. We distinguish threshold-free deadline ranking from validation-selected fixed-policy alarm performance and evaluate prediction horizons and encoder architectures. TLS achieves the best mean alarm performance on DIII-D and EAST, whereas all methods perform poorly on Alcator C-Mod. survTLS does not consistently outperform DSM, suggesting that directly learning horizon-level event probability is more effective than modeling detailed within-horizon event-time distributions in the present setting. Finally, the selected prediction horizons and encoder-ablation results vary across devices, reflecting differences in disruption characteristics.

Poloidal asymmetries of main chamber neutral fueling in DIII-D ELMy H-mode plasmas

Laszlo Horvath, Florian Laggner, Raúl Gerrú, Filippo Scotti, Alessandro Bortolon, Eric Emdee, Shaun R Haskey, Ryan Hood, Jerry W Hughes, Tomas Odstrcil, et al.

Understanding poloidal asymmetries in main chamber neutral fueling is essential for characterizing the balance between particle sources and transport in the formation of the H-mode density pedestal. The primary goal of this work is to study changes in these fueling asymmetries and their relationship to divertor recycling across different magnetic configurations in DIII-D lower single-null type-I ELMy H-mode plasmas, using direct measurements of the pedestal ionization source obtained with the LLAMA (Lyman-alpha Measurement Apparatus) diagnostic. By combining these direct measurements of the neutral population and studying how it influences the pedestal density structure and overall pedestal performance, this work aims to provide new insights into the role of neutrals in H-mode pedestal physics. We find that the main chamber ionization on the high-field-side (HFS) strongly dominates when the ion ∇B drift is in the favorable direction. In contrast, reversing the drift direction to the unfavorable direction significantly reduces HFS fueling, that is only partially compensated by a moderate increase in low-field-side (LFS) fueling. The resulting changes in the edge particle source are accompanied by a decrease in pedestal electron density and an increase in pedestal temperature, such that the pedestal pressure remains approximately unchanged. Measurements of divertor recycling and divertor radiation indicate that these fueling asymmetries are also linked to the divertor regime. In particular, inner divertor detachment in the favorable drift configuration decouples main chamber fueling on the HFS from target recycling, while attached divertor conditions in unfavorable drift cases lead to a strong correlation between divertor recycling and main chamber fueling asymmetries. These results suggest that the ion ∇B drift direction, by modifying main chamber fueling, can influence the pedestal density structure and overall pedestal performance.

First Experimental Evidence of Helicon Current Drive

J. B. Lestz, R. I. Pinsker, B. Van Compernolle, S. X. Tang, A. Dupuy, A. M. Garofalo, L. McAllister, C. P. Moeller, C. C. Petty, M. Porkolab, et al.

Helicon current drive is an attractive solution for driving current to sustain steady state tokamak operation in reactor conditions. Dedicated DIII-D experiments have been conducted with a MW-level helicon system and successfully demonstrated core power deposition and current drive with helicon waves launched via a traveling wave antenna. The profile of the measured electron temperature response to helicon power injection is in good agreement with time-dependent integrated modeling that incorporates ray tracing and the effects of thermal transport simultaneously. When the helicon power is injected continuously to drive co-$I_p$ current, the reconstructed safety factor profile flattens significantly faster and sawteeth are triggered earlier than in comparison shots where the helicon is replaced by a comparable amount of electron cyclotron heating. Calculation of the helicon-driven current profile yields a peaked profile in the core, consistent with the observed power deposition profile and in good agreement with ray tracing predictions. Taken together, these experimental results represent strong evidence for the first definitive observation of auxiliary current drive due to helicon waves on any device.

Exploration of an intrinsic low-collisionality, high performance, grassy ELM regime in the DIII-D tokamak

Zeyu Li, H Q Wang, Xi Chen, Xueqiao Xu, Rongjie Hong, Filipp Khabanov, V. S. Chan, Patrick H Diamond, Brian S Victor, Nami Li, et al.

Recent DIII-D tokamak experiments have demonstrated the integration of intrinsic low-collisionality grassy edge-localized mode (ELM) regime with high-performance hybrid core scenario, possibly offering a core-edge compatible solution for ITER and future fusion reactors. This regime features grassy ELMs (with ELM energy loss over pedestal stored energy <2%) at ITER-relevant pedestal top collisionality (ν_e^*~0.1), ITER similar shape, while maintaining high core confinement (H_98y2~1.5) in non-inductive hybrid scenarios. A small ELM-focused database is constructed to investigate the parametric dependence of the small/grassy ELM regimes. Access and sustainment of this regime appear to be favored by high poloidal beta (β_p>1.5), higher ratio of separatrix-to-pedestal density (n_(e,sep)⁄n_(e,ped) >0.4) and low pedestal top collisionality (υ_(e,ped)^*=0.1-0.4). In this scenario, the pedestal width exceeds the prediction from EPED–KBM scaling, consistent with the expectation of a turbulence-limited pedestal. Linear modeling using ELITE indicates that this grassy ELM regime is along the peeling boundary. Relative to a large-ELM phase, the grassy-ELM phase exhibits a broader inner-target heat-flux width and a substantially reduced ELM-induced transient heat-flux increment. These results motivate further evaluation of low-collisionality grassy ELMs as a potentially reactor-relevant operating regime, while full-duration sustainment and compatibility with divertor detachment remain unresolved.

Assessing the effect of error field penetration during plasma current ramp-up in the DIII-D tokamak

C. F. B. Zimmermann, E. M. Bursch, C. Paz-Soldan, J. M. Hanson, N. Leuthold, N. C. Logan, A. O. Nelson

This work provides evidence that established error field penetration threshold scalings remain applicable during plasma current ramp-up. In dedicated DIII-D experiments with imposed $n=1$ perturbations during extended $I_p$ ramps, an apparent empirical threshold is found between $2$ and $3$~kA of applied 3D coil current, above which MHD modes are seeded. The imposed perturbation couples to the rational surfaces present during the ramp, seeding near the $q=4$ surface and penetrating as an $m/n=3/1$ mode by the end of the perturbation phase. To interpret these observations, multi-machine penetration threshold scalings are combined with equilibrium-based overlap metrics from the GPEC code, including the in-situ error fields of the device. This modeling reproduces the observed onset in the amplitude scan and classifies mode seeding across a database of 12 ramp-up discharges spanning a range of plasma currents and densities. Across this database, the seeding appears to be controlled primarily by the applied 3D coil current rather than by the plasma current or its ramp rate. Accounting for the in-situ error fields is found to be important for reliable prediction. These results are consistent with the robustness of scaling-based penetration metrics when coupled to detailed 3D field modeling under transient ramp-up conditions, and suggest the importance of accounting for in-situ error fields when assessing additional externally induced perturbations. This work is motivated by future tokamaks in which transient, non-axisymmetric error fields can arise during startup, for example from runaway electron mitigation coils.

The Fusion Equilibrium Challenge: Inferring Magnetic Geometry Without Magnetic Diagnostics

Tapan Ganatma Nakkina, Matthew Waller, Craig Michoski, Brian Sammuli, David R. Hatch, William Boyes, Mitchell Clark, Raffi Nazikian, Sterling Smith

Next-generation fusion reactor devices such as SPARC, ARC, and CFETR will operate in extreme neutron environments that compromise the magnetic sensors traditionally used to reconstruct plasma equilibria. However, reliable knowledge of the plasma equilibrium--including magnetic flux surfaces, safety factor profiles, and shaping parameters--is indispensable for real-time control, disruption avoidance, and physics interpretation. The Fusion Equilibrium Challenge invites the NeurIPS community to confront a deceptively simple but scientifically rigorous inverse problem: reconstruct the two-dimensional poloidal flux function psi(R,Z) and a suite of scalar equilibrium parameters from non-magnetic diagnostics alone, namely external poloidal-field coil currents and Thomson-scattering electron temperature/density profiles. The challenge provides the first open-access, harmonized multi-machine benchmark for fusion, releasing a curated dataset of 9,113 DIII-D shots and 2,416 MAST shots--filtered for Thomson-diagnostic availability, feature completeness, and EFIT-reconstruction quality. Each shot is packaged into a standard Parquet file containing approximately 260 (DIII-D) / approximately 80 (MAST) EFIT flux maps and rich high-rate diagnostics. Two complementary awards reward intra-machine reconstruction fidelity (S_model) on DIII-D and zero-shot cross-machine generalization (G_ratio) to the topologically distinct MAST spherical tokamak. We argue that the challenge functions as a benchmark for reactor-ready equilibrium inference and as a probe of how far machine learning can be pushed toward truly machine-agnostic plasma state estimation.

ELMO: An Uncertainty-Aware Simulation-to-Surrogate Workflow for Fast Pedestal Linear-Stability Prediction

Nami Li, X. Q. Xu, T. Osborne, E. Suchyta, Y. C. Fu, N. Podhorszki, H. Wang, Z. Li

Rapid prediction of pedestal linear stability is important for exploring tokamak operating space, uncertainty quantification, and future model-informed control, but mode-resolved magnetohydrodynamic stability calculations using BOUT++ are computationally expensive. We present a focused implementation of ELMO--the Edge Learning and Modeling Orchestrator--as an uncertainty-aware simulation-to-surrogate workflow integrating equilibrium generation, field-aligned mesh construction, large-scale BOUT++ calculations, automated campaign execution and data reduction, and Gaussian Process Regression (GPR). For a single DIII-D plasma shape, 3,869 of 7,992 requested configurations completed equilibrium reconstruction, mesh generation, stability calculation, and quality control. Each retained equilibrium was evaluated at sixteen toroidal mode numbers, $n=5$--80 with $Δn=5$, using ideal-MHD and ideal-plus-diamagnetic models, producing 123,808 mode-resolved calculations. Using eight pedestal features, the GPR surrogate predicts two sixteen-mode growth-rate spectra with latent posterior uncertainty estimates. Across five independent test realizations, the maximum-growth-rate prediction achieved $R^2=0.978\pm0.013$ for ideal MHD and $R^2=0.966\pm0.009$ for ideal-plus-diamagnetic physics. The surrogate reproduces the spectral shape and dominant unstable mode. Calibration diagnostics indicate that posterior uncertainties are useful for relative acquisition but are underdispersed and should not be interpreted as calibrated prediction intervals. Prediction of all 32 outputs requires about 20 ms on one CPU core, compared with about 21 min using 128 CPU cores for the corresponding BOUT++ scan, giving a $6.3\times10^4$-fold wall-clock speedup and an $8.1\times10^6$-fold reduction in computational cost.

Characterization of ELM Pacing via Vertical Jogs on DIII-D

Kei Yasoda, Dario Giovanni Panici, Andrew Oakleigh Nelson, Florian M Laggner, SangKyeun Kim, Egemen Kolemen

Edge localized mode (ELM) pacing via vertical plasma oscillations—or "jogging"—has been successfully demonstrated on the DIII-D tokamak. Rapid vertical movement of the plasma toward the X-point effectively triggers ELMs. By vertically oscillating the plasma at 10 Hz, the ELM frequency increased from its natural rate of ∼5 Hz in similar DIII-D discharges to 10 Hz. Notably, downward jogs have been observed to trigger multiple ELMs in a single cycle. ELMs triggered at these higher-than-natural frequencies lead to smaller decreases in stored energy, dropping from 10% to below 1%. Consequently, the peak heat flux to the divertor is reduced by a factor of ∼2, alongside an observed reduction in carbon impurity concentration. During downward jogs in the lower single null (LSN) configuration, the X-point movement is slower and smaller than the top of the plasma, resulting in a reduced plasma cross-section and volume. To understand the mechanism of ELM triggering by jogging, a model of the edge toroidal current was developed and tested against DIII-D experimental data. Both the data and the model suggest that moving the plasma toward the X-point locally induces a net positive toroidal current in the edge region. ELITE stability analysis indicates that this induced current pushes the plasma state across the peeling side of the peeling-ballooning stability boundary into the unstable region, triggering the ELMs.

Effect of electron cyclotron waves on plasma with runaway electrons

Pavel Aleynikov, Alexander Franklin Battey, Carlos Paz-Soldan, Eric Matthias Hollmann, Andrey Lvovskiy, Claudio Marini, Daisuke Shiraki, Charles Lasnier

Runaway electrons generated during tokamak disruptions are a major concern for the safe operation of future fusion devices. The interaction of runaway electrons with waves has been proposed as a potential mechanism for their mitigation. This study investigates the effect of electron-cyclotron (EC) waves on post-disruption plasmas containing runaway electrons (REs). O- and X-mode EC waves are routinely used for plasma heating and current drive. However, these modes do not interact directly with relativistic electrons and cannot be injected into plasmas with densities exceeding their respective cutoff densities. In contrast, the internal slow X-mode (sX) can resonate with relativistic electrons and may therefore provide a pathway for their mitigation. We report DIII-D experiments designed to access the internal slow X-mode through O--sX conversion during post-disruption RE plateaus. ECH increased the background-plasma density, doubled the loop voltage, and strongly enhanced the RE synchrotron signal, demonstrating substantial ECH--plasma coupling and increased effective dissipation of the RE channel. Although ECH produced a pronounced response consistent with enhanced RE dissipation, we could not isolate conclusive evidence of resonant sX--RE interaction. Strong heating, ionization, and impurity-redistribution effects appear to dominate the response and may mask a direct wave--particle signature. Nevertheless, the results demonstrate the potential of ECH for RE control through background-plasma modification, with O--sX access offering an additional possibility of direct resonant interaction.

Fast-ion enhanced modeling of neoclassical tearing modes at NSTX and DIII-D

James Yang, Eric Fredrickson, John W Berkery, Robert John La Haye, Mario Podesta

A new framework for the solution of modified Rutherford equation including fast ions is successfully applied to interpret the tearing mode stability of two discharges NSTX #134020 and DIII-D #135861. The simulated island width growth rates are in better agreement with the measured island growth rate when the fast ions are included. While constants are multiplied to the polarization current contribution terms for NSTX #134020, no constants are necessary to match the simulated and measured island width growth rates for DIII-D #135861. The estimated island frequencies appear to provide an explanation of the different constants used in the two discharges. The gradient scale lengths suggest that the fast ion contribution can become significant in plasmas with flat thermal ion density profile and steep fast ion density profile.

First Observation of Currents Induced by Alfvén Eigenmodes in a Magnetic Confinement Device

W. W. Heidbrink, X. D. Du, M. E. Austin, K. J. Callahan, C. T. Holcomb, J. B. Lestz, L. Liu, G. R. McKee, L. Schmitz, M. A. Van Zeeland, et al.

Radial phase variation and energy flow of Alfvén gap modes

Xinran Xu, Jian Bao, Wenlu Zhang, Chao Dong, Jintao Cao, Ding Li

Radially curved mode structures of Alfvén eigenmodes are commonly observed in fusion experiments associated with energy transport, which indicate the radial phase variation arising from non-ideal magnetohydrodynamics (MHD) and global effects. In this work, based on MAS global eigenvalue simulations with Landau-fluid bulk plasmas and non-perturbative gyrokinetic energetic ions, we investigate the physical mechanisms responsible for the curved poloidal mode structure tail of RSAE and the rapid phase change of radially coupled RSAE and TAE in DIII-D plasmas. The former one is due to kinetic interaction between RSAE and Alfvén continuum with enhanced mode conversion to kinetic Alfvén waves, and the latter one can be explained by global effects of higher-order radial eigenstate or RSAE-TAE hybrid modes with multiple poloidal harmonics. An improved energy transport model based on global mode structures is formulated and implemented in the MAS framework, which clearly demonstrates the radial phase variation and EI non-perturbative effects on the radial Poynting vector.

Non-dimensional confinement scaling in similar negative triangularity plasmas on the DIII-D and TCV tokamaks

Alessandro Marinoni, Colin Chrystal, Stefano Coda, Reinart Coosemans, Claudio Marini, Mario Podesta, Olivier Sauter, Matteo Agostini, Max E Austin, Emily A Belli, et al.

Similarity experiments were performed on the DIII-D and TCV tokamaks to explore the scaling of energy confinement in negative triangularity plasmas using non-dimensional variables. Near up-down symmetric plasmas with large top-bottom averaged negative triangularity were created in a lower single null configuration, with the shape of the separatrix being closely matched between the two devices. The normalized energy confinement is found to weakly improve at increasing collisionality and, between the two devices, shows a machine size scaling behavior between Bohm and gyro-Bohm. Engineering scaling on a large DIII-D dataset is in agreement with the non-dimensional experiment.

Multi-diagnostic characterization of neutrals in the confined region of DIII-D using interpretive DEGAS2 simulations

Quinn Pratt, Shaun R Haskey, George Wilkie, Laszlo Horvath, Raúl Gerrú, Gilson Ronchi, Mathias Groth

Measurements from multiple diagnostics are combined to constrain the density of neutrals in the confined plasma and improve our understanding of edge particle sources. Passive D α emission spectrum measurements are obtained along tangential views at the plasma midplane and near the X-point. Spectral D α measurements provide a strong constraint on the neutral population through energy information in the wavelength distribution of emission. The two-dimensional distribution of neutrals is calculated using interpretive DEGAS2 neutral transport simulations with a plasma background based largely on 1D profiles and magnetic equilibrium reconstruction. DEGAS2 is used as a forward model to predict the emission measured along various lines of sight. We demonstrate two approaches for calibrating DEGAS2 simulations to match spectral emission measurements: (1) fitting the strength of neutral sources at the simulation boundary, and (2) optimizing the plasma background in the pedestal/SOL. Traditional filter-based measurements of D α and Ly α emission are used to validate the calibrated DEGAS2 case at multiple poloidal locations. Once calibrated, DEGAS2 is able to match the measurements generally within a factor of 2, garnering confidence in our diagnostic models and the physics included in DEGAS2. The experimentally constrained 2D neutral distribution is used to quantitatively study particle transport. We report the flux surface averaged neutral density and (main ion) particle source for a standard DIII-D H-mode plasma. In the pedestal, the particle source is found to be primarily driven by divertor neutral sources (recycling). However, neutrals originating in the main chamber play a significant role further inside the plasma. We find the global (main ion) particle confinement time to be τ p,D+ ≈ 130 ms (τ p,D+ ≈ τ E /2). Finally, we present evidence for poloidal asymmetries in the plasma, including decreased main ion temperature above the X-point, and a high density region above the inner target.