Showing 1–18 of 18 results for author: Dawson, W

LARA: Validation-Driven Agentic Supercomputer Workflows for Atomistic Modeling

Authors: William Dawson, Louis Beal, Yoann Curé, Giuseppe Fisicaro, Dorian Rolland, Luigi Genovese

Abstract: Large language models (LLMs) and agentic systems have recently demonstrated potential for automating scientific workflows, including atomistic simulations. However, their deployment in high-performance computing (HPC) environments remains limited by the lack of mechanisms ensuring correctness, reproducibility, and safe interaction with computational resources. Generated workflows suffer from incon… ▽ More Large language models (LLMs) and agentic systems have recently demonstrated potential for automating scientific workflows, including atomistic simulations. However, their deployment in high-performance computing (HPC) environments remains limited by the lack of mechanisms ensuring correctness, reproducibility, and safe interaction with computational resources. Generated workflows suffer from inconsistencies, incorrect API usage, or invalid physical configurations - leading to failed or unreliable simulations. In this work, we introduce LARA-HPC, a validation-driven agentic framework to enable reliable workflow generation for atomistic modeling on HPC systems. Our approach is based on three key components: (i) a controlled execution layer that mediates all interactions with HPC resources; (ii) simulation-native validation through dry-run capabilities, enabling execution-level verification without incurring resource cost; and (iii) a multi-phase agentic pipeline combining retrieval-augmented generation and iterative refinement. We demonstrate the effectiveness of this approach performing an end-to-end atomistic simulation workflow on HPC by applying LARA-HPC to Density Functional Theory simulations. The results show that validation-driven generation significantly improves robustness and enables iterative correction of both syntactic and physical inconsistencies. More broadly, this work advocates for a shift from generation-first to validation-first paradigms in Artificial Intelligence (AI) assisted scientific computing. We argue that the future task of the computational physics community is to develop domain specific agentic systems based on structured tooling to realize an HPC enabled co-piloted research ecosystem. △ Less

Submitted 24 April, 2026; originally announced April 2026.

Comments: 12 pages, 2 figures

Coupling Quantum Mechanical Modeling and Molecular Dynamics on Heterogeneous Supercomputers for Studying Distal Mutation Effects on Drug Binding in HIV-1

Authors: William Dawson, Louis Beal, Marco Zaccaria, Luigi Genovese

Abstract: Predicting how protein mutations affect drug binding remains a major challenge, particularly when the mutations are distal from the binding site. In this study, we introduce a coupled simulation workflow that combines long-time-scale molecular dynamics (MD) with high-throughput quantum mechanical (QM) analysis to reveal the electronic structure signatures of mutation induced drug resistance in the… ▽ More Predicting how protein mutations affect drug binding remains a major challenge, particularly when the mutations are distal from the binding site. In this study, we introduce a coupled simulation workflow that combines long-time-scale molecular dynamics (MD) with high-throughput quantum mechanical (QM) analysis to reveal the electronic structure signatures of mutation induced drug resistance in the HIV-1 protease. Our workflow leverages GPU-accelerated MD to generate conformational ensembles, and performs in-operando linear-scaling density functional theory (DFT) calculations on selected frames parallelized on a coupled partition of CPU nodes. This design enables efficient, massively parallel quantum analysis of protein-ligand complexes at atomic resolution. Using this approach, we investigate resistance to the antiviral Darunavir in a multi-mutant HIV-1 protease variant. By mapping the network of electronic interactions across the binding interface, our results highlight the critical role of conformational sampling and quantum insight in understanding distal mutation effects, and demonstrate a scalable computational strategy for studying complex biophysical mechanisms of drug resistance. We argue that such kind of analysis may pave the way for designing inhibitors that maintain binding stability against systemic, mutation-induced destabilization. △ Less

Submitted 27 March, 2026; originally announced March 2026.

Comments: 22 pages, 11 figures

Roadmap on Advancements of the FHI-aims Software Package

Authors: Joseph W. Abbott, Carlos Mera Acosta, Alaa Akkoush, Alberto Ambrosetti, Viktor Atalla, Alexej Bagrets, Jörg Behler, Daniel Berger, Hannah Bertschi, Björn Bieniek, Jonas Björk, Volker Blum, Saeed Bohloul, Connor L. Box, Nicholas Boyer, Danilo Simoes Brambila, Gabriel A. Bramley, Kyle R. Bryenton, María Camarasa-Gómez, Christian Carbogno, Fabio Caruso, Sucismita Chutia, Michele Ceriotti, Gábor Csányi, William Dawson , et al. (181 additional authors not shown)

Abstract: Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, reliable predictions are unlikely at any level that follows. The software package FHI-aims has proven to be a game changer for accurate free-energy calculations because of its scalability, numerical precis… ▽ More Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, reliable predictions are unlikely at any level that follows. The software package FHI-aims has proven to be a game changer for accurate free-energy calculations because of its scalability, numerical precision, and its efficient handling of density functional theory (DFT) with hybrid functionals and van der Waals interactions. It treats molecules, clusters, and extended systems (solids and liquids) on an equal footing. Besides DFT, FHI-aims also includes quantum-chemistry methods, descriptions for excited states and vibrations, and calculations of various types of transport. Recent advancements address the integration of FHI-aims into an increasing number of workflows and various artificial intelligence (AI) methods. This Roadmap describes the state-of-the-art of FHI-aims and advancements that are currently ongoing or planned. △ Less

Submitted 20 April, 2026; v1 submitted 30 April, 2025; originally announced May 2025.

Comments: arXiv admin note: Includes articles arXiv:2502.02460, arXiv:2501.02550, arXiv:2411.01680, arXiv:2501.16091, arXiv:2411.04951

A Scalable Diagonalization Framework for Tensor-Product Bitstring Selected Configuration Interaction

Authors: Enhua Xu, William Dawson, Himadri Pathak, Takahito Nakajima

Abstract: Selected configuration interaction (SCI) methods are effective for treating strongly correlated electronic systems, yet their scalability has long been limited by implementations that replicate the configuration interaction (CI) vector across processes, leading to severe memory bottlenecks. Here, we present a fully distributed diagonalization framework tailored for extremely large selected determi… ▽ More Selected configuration interaction (SCI) methods are effective for treating strongly correlated electronic systems, yet their scalability has long been limited by implementations that replicate the configuration interaction (CI) vector across processes, leading to severe memory bottlenecks. Here, we present a fully distributed diagonalization framework tailored for extremely large selected determinant spaces, directly addressing this major scalability bottleneck of modern SCI methods. The method is grounded in a tensor-product bitstring (TPB) representation, in which determinants are organized through a TPB structure constructed from selected alpha- and beta-bitstrings, and is referred to as tensor-product bitstring SCI (TBSCI). An efficient TBSCI eigensolver is developed based on a novel bitstring-based Hamiltonian evaluation algorithm together with a suite of MPI communication strategies designed to improve parallel efficiency. Large-scale full configuration interaction (FCI) benchmarks, employed as communication-intensive stress tests, demonstrate that the implemented TBSCI eigensolver continues to reduce the wall time for distributed diagonalization of 2.6 trillion determinants, reaching 54,000 nodes (more than 2.5 million cores) on supercomputer Fugaku. Beyond scalability, we investigate the structural compactness of the TPB representation and show that selecting alpha- and beta-bitstrings according to their collective weights in a reference SCI wavefunction yields TPB-based wavefunctions approaching the FCI limit while using only a small fraction of determinants. These results establish TBSCI as a scalable SCI methodology and provide evidence for the intrinsic compactness of the TPB representation. △ Less

Submitted 29 April, 2026; v1 submitted 13 March, 2025; originally announced March 2025.

Journal ref: J. Chem. Phys. 164, 194103 (2026)

Solvers for Large-Scale Electronic Structure Theory: ELPA and ELSI

Authors: Petr Karpov, Andreas Marek, Tobias Melson, Alexander Pöppl, Victor Wen-zhe Yu, Ben Hourahine, Alberto Garcia, William Dawson, Yi Yao, William Huhn, Jonathan Moussa, Sam Hall, Reinhard Maurer, Uthpala Herath, Konstantin Lion, Sebastian Kokott, Volker Blum

Abstract: In this contribution, we give an overview of the ELPA library and ELSI interface, which are crucial elements for large-scale electronic structure calculations in FHI-aims. ELPA is a key solver library that provides efficient solutions for both standard and generalized eigenproblems, which are central to the Kohn-Sham formalism in density functional theory (DFT). It supports CPU and GPU architect… ▽ More In this contribution, we give an overview of the ELPA library and ELSI interface, which are crucial elements for large-scale electronic structure calculations in FHI-aims. ELPA is a key solver library that provides efficient solutions for both standard and generalized eigenproblems, which are central to the Kohn-Sham formalism in density functional theory (DFT). It supports CPU and GPU architectures, with full support for NVIDIA and AMD GPUs, and ongoing development for Intel GPUs. Here we also report the results of recent optimizations, leading to significant improvements in GPU performance for the generalized eigenproblem. ELSI is an open-source software interface layer that creates a well-defined connection between "user" electronic structure codes and "solver" libraries for the Kohn-Sham problem, abstracting the step between Hamilton and overlap matrices (as input to ELSI and the respective solvers) and eigenvalues and eigenvectors or density matrix solutions (as output to be passed back to the "user" electronic structure code). In addition to ELPA, ELSI supports solvers including LAPACK and MAGMA, the PEXSI and NTPoly libraries (which bypass an explicit eigenvalue solution), and several others. △ Less

Submitted 4 February, 2025; originally announced February 2025.

Comments: Contribution to the upcoming Roadmap for Advancements of the FHI-aims Software Package

Reducing Numerical Precision Requirements in Quantum Chemistry Calculations

Authors: William Dawson, Katsuhisa Ozaki, Jens Domke, Takahito Nakajima

Abstract: The abundant demand for deep learning compute resources has created a renaissance in low precision hardware. Going forward, it will be essential for simulation software to run on this new generation of machines without sacrificing scientific fidelity. In this paper, we examine the precision requirements of a representative kernel from quantum chemistry calculations: calculation of the single parti… ▽ More The abundant demand for deep learning compute resources has created a renaissance in low precision hardware. Going forward, it will be essential for simulation software to run on this new generation of machines without sacrificing scientific fidelity. In this paper, we examine the precision requirements of a representative kernel from quantum chemistry calculations: calculation of the single particle density matrix from a given mean field Hamiltonian (i.e. Hartree-Fock or Density Functional Theory) represented in an LCAO basis. We find that double precision affords an unnecessarily high level of precision, leading to optimization opportunities. We show how an approximation built from an error-free matrix multiplication transformation can be used to potentially accelerate this kernel on future hardware. Our results provide a road map for adapting quantum chemistry software for the next generation of High Performance Computing platforms. △ Less

Submitted 22 October, 2024; v1 submitted 18 July, 2024; originally announced July 2024.

Exploratory Data Science on Supercomputers for Quantum Mechanical Calculations

Authors: William Dawson, Louis Beal, Laura E. Ratcliff, Martina Stella, Takahito Nakajima, Luigi Genovese

Abstract: Literate programming - the bringing together of program code and natural language narratives - has become a ubiquitous approach in the realm of data science. This methodology is appealing as well for the domain of Density Functional Theory (DFT) calculations, particularly for interactively developing new methodologies and workflows. However, effective use of literate programming is hampered by old… ▽ More Literate programming - the bringing together of program code and natural language narratives - has become a ubiquitous approach in the realm of data science. This methodology is appealing as well for the domain of Density Functional Theory (DFT) calculations, particularly for interactively developing new methodologies and workflows. However, effective use of literate programming is hampered by old programming paradigms and the difficulties associated with using High Performance Computing (HPC) resources. Here we present two Python libraries that aim to remove these hurdles. First, we describe the PyBigDFT library, which can be used to setup materials or molecular systems and provides high-level access to the wavelet based BigDFT code. We then present the related remotemanager library, which is able to serialize and execute arbitrary Python functions on remote supercomputers. We show how together these libraries enable transparent access to HPC based DFT calculations and can serve as building blocks for rapid prototyping and data exploration. △ Less

Submitted 14 October, 2023; originally announced October 2023.

Complexity Reduction in Density Functional Theory: Locality in Space and Energy

Authors: William Dawson, Eisuke Kawashima, Laura E. Ratcliff, Muneaki Kamiya, Luigi Genovese, Takahito Nakajima

Abstract: We present recent developments of the NTChem program for performing large scale hybrid Density Functional Theory calculations on the supercomputer Fugaku. We combine these developments with our recently proposed Complexity Reduction Framework to assess the impact of basis set and functional choice on its measures of fragment quality and interaction. We further exploit the all electron representati… ▽ More We present recent developments of the NTChem program for performing large scale hybrid Density Functional Theory calculations on the supercomputer Fugaku. We combine these developments with our recently proposed Complexity Reduction Framework to assess the impact of basis set and functional choice on its measures of fragment quality and interaction. We further exploit the all electron representation to study system fragmentation in various energy envelopes. Building off this analysis, we propose two algorithms for computing the orbital energies of the Kohn-Sham Hamiltonian. We demonstrate these algorithms can efficiently be applied to systems composed of thousands of atoms and as an analysis tool that reveals the origin of spectral properties. △ Less

Submitted 28 April, 2023; v1 submitted 16 January, 2023; originally announced January 2023.

Comments: Accepted Manuscript

Journal ref: J. Chem. Phys. 158, 164114 (2023)

Roadmap on Electronic Structure Codes in the Exascale Era

Authors: Vikram Gavini, Stefano Baroni, Volker Blum, David R. Bowler, Alexander Buccheri, James R. Chelikowsky, Sambit Das, William Dawson, Pietro Delugas, Mehmet Dogan, Claudia Draxl, Giulia Galli, Luigi Genovese, Paolo Giannozzi, Matteo Giantomassi, Xavier Gonze, Marco Govoni, Andris Gulans, François Gygi, John M. Herbert, Sebastian Kokott, Thomas D. Kühne, Kai-Hsin Liou, Tsuyoshi Miyazaki, Phani Motamarri , et al. (16 additional authors not shown)

Abstract: Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources d… ▽ More Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing. △ Less

Submitted 26 September, 2022; originally announced September 2022.

Comments: Submitted as a roadmap article to Modelling and Simulation in Materials Science and Engineering; Address any correspondence to Vikram Gavini (vikramg@umich.edu) and Danny Perez (danny_perez@lanl.gov)

Probing Disorder in 2CzPN using Core and Valence States

Authors: Nathalie K. Fernando, Martina Stella, William Dawson, Takahito Nakajima, Luigi Genovese, Anna Regoutz, Laura E. Ratcliff

Abstract: Molecules which exhibit thermally activated delayed fluorescence (TADF) show great promise for use in efficient, environmentally-friendly OLEDs, and thus the design of new TADF emitters is an active area of research. However, when used in devices, they are typically in the form of disordered thin films, where both the external molecular environment and thermally-induced internal variations in para… ▽ More Molecules which exhibit thermally activated delayed fluorescence (TADF) show great promise for use in efficient, environmentally-friendly OLEDs, and thus the design of new TADF emitters is an active area of research. However, when used in devices, they are typically in the form of disordered thin films, where both the external molecular environment and thermally-induced internal variations in parameters such as the torsion angle can strongly influence their electronic structure. In this work, we use density functional theory and X-ray photoelectron spectroscopy to investigate the impact of disorder on both core and valence states in the TADF emitter 2CzPN. By simulating gas phase molecules displaying varying levels of disorder, we assess the relative sensitivity of the different states to factors such as varying torsion angle. The theoretical results for both core and valence states show good agreement with experiment, thereby also highlighting the advantages of our approach for interpreting experimental spectra of large aromatic molecules, which are too complex to interpret based solely on experimental data. △ Less

Submitted 10 June, 2022; originally announced June 2022.

A Reanalysis of Public Galactic Bulge Gravitational Microlensing Events from OGLE-III and IV

Authors: Nathan Golovich, William A. Dawson, Fran Bartolić, Casey Y. Lam, Jessica R. Lu, Michael S. Medford, Michael D. Schneider, George Chapline, Edward F. Schlafly, Alex Drlica-Wagner, Kerianne Pruett

Abstract: Modern surveys of gravitational microlensing events have progressed to detecting thousands per year. Surveys are capable of probing Galactic structure, stellar evolution, lens populations, black hole physics, and the nature of dark matter. One of the key avenues for doing this is studying the microlensing Einstein radius crossing time distribution ($t_E$). However, systematics in individual light… ▽ More Modern surveys of gravitational microlensing events have progressed to detecting thousands per year. Surveys are capable of probing Galactic structure, stellar evolution, lens populations, black hole physics, and the nature of dark matter. One of the key avenues for doing this is studying the microlensing Einstein radius crossing time distribution ($t_E$). However, systematics in individual light curves as well as over-simplistic modeling can lead to biased results. To address this, we developed a model to simultaneously handle the microlensing parallax due to Earth's motion, systematic instrumental effects, and unlensed stellar variability with a Gaussian Process model. We used light curves for nearly 10,000 OGLE-III and IV Milky Way bulge microlensing events and fit each with our model. We also developed a forward model approach to infer the timescale distribution by forward modeling from the data rather than using point estimates from individual events. We find that modeling the variability in the baseline removes a source of significant bias in individual events, and previous analyses over-estimated the number of long timescale ($t_E>100$ days) events due to their over simplistic models ignoring parallax effects and stellar variability. We use our fits to identify hundreds of events that are likely black holes. △ Less

Submitted 16 September, 2020; originally announced September 2020.

Comments: Submitted version, in review, 33 pages, 18 figures, MCMC posterior samples available by publisher after acceptance

ELSI -- An Open Infrastructure for Electronic Structure Solvers

Authors: Victor Wen-zhe Yu, Carmen Campos, William Dawson, Alberto García, Ville Havu, Ben Hourahine, William P Huhn, Mathias Jacquelin, Weile Jia, Murat Keçeli, Raul Laasner, Yingzhou Li, Lin Lin, Jianfeng Lu, Jonathan Moussa, Jose E Roman, Álvaro Vázquez-Mayagoitia, Chao Yang, Volker Blum

Abstract: Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infi… ▽ More Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infinite periodic boundary conditions) yield matrices with different structures. The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. In this paper, we present recent improvements and developments inside ELSI, mainly covering (1) new solvers connected to the interface, (2) matrix layout and communication adapted for parallel calculations of periodic and/or spin-polarized systems, (3) routines for density matrix extrapolation in geometry optimization and molecular dynamics calculations, and (4) general utilities such as parallel matrix I/O and JSON output. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on results of a systematic set of large-scale benchmarks performed with Kohn-Sham density-functional theory and density-functional tight-binding theory, we identify factors that strongly affect the efficiency of the solvers, and propose a decision layer that assists with the solver selection process. Finally, we describe a reverse communication interface encoding matrix-free iterative solver strategies that are amenable, e.g., for use with planewave basis sets. △ Less

Submitted 4 July, 2020; v1 submitted 31 December, 2019; originally announced December 2019.

Journal ref: Computer Physics Communications 256 (2020) 107459

Complexity Reduction in Density Functional Theory Calculations of Large Systems: System Partitioning and Fragment Embedding

Authors: William Dawson, Stephan Mohr, Laura E. Ratcliff, Takahito Nakajima, Luigi Genovese

Abstract: With the development of low order scaling methods for performing Kohn-Sham Density Functional Theory, it is now possible to perform fully quantum mechanical calculations of systems containing tens of thousands of atoms. However, with an increase in the size of system treated comes an increase in complexity, making it challenging to analyze such large systems and determine the cause of emergent pro… ▽ More With the development of low order scaling methods for performing Kohn-Sham Density Functional Theory, it is now possible to perform fully quantum mechanical calculations of systems containing tens of thousands of atoms. However, with an increase in the size of system treated comes an increase in complexity, making it challenging to analyze such large systems and determine the cause of emergent properties. To address this issue, in this paper we present a systematic complexity reduction methodology which can break down large systems into their constituent fragments, and quantify inter-fragment interactions. The methodology proposed here requires no a priori information or user interaction, allowing a single workflow to be automatically applied to any system of interest. We apply this approach to a variety of different systems, and show how it allows for the derivation of new system descriptors, the design of QM/MM partitioning schemes, and the novel application of graph metrics to molecules and materials. △ Less

Submitted 30 March, 2020; v1 submitted 19 November, 2019; originally announced November 2019.

Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library

Authors: Stephan Mohr, William Dawson, Michael Wagner, Damien Caliste, Takahito Nakajima, Luigi Genovese

Abstract: We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary power… ▽ More We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary powers, and the extraction of eigenvalues in a selected interval. CheSS is able to exploit the sparsity of the matrices and scales linearly with respect to the number of nonzero entries, making it well-suited for large-scale calculations. The approach is particularly adapted for setups leading to small spectral widths of the involved matrices and outperforms alternative methods in this regime. By coupling CheSS to the DFT code BigDFT, we show that such a favorable setup is indeed possible in practice. In addition, the approach based on Chebyshev polynomials can be massively parallelized, and CheSS exhibits excellent scaling up to thousands of cores even for relatively small matrix sizes. △ Less

Submitted 10 October, 2017; v1 submitted 3 April, 2017; originally announced April 2017.

Blind Detection of Ultra-faint Streaks with a Maximum Likelihood Method

Authors: William A. Dawson, Michael D. Schneider, Chandrika Kamath

Abstract: We have developed a maximum likelihood source detection method capable of detecting ultra-faint streaks with surface brightnesses approximately an order of magnitude fainter than the pixel level noise. Our maximum likelihood detection method is a model based approach that requires no a priori knowledge about the streak location, orientation, length, or surface brightness. This method enables disco… ▽ More We have developed a maximum likelihood source detection method capable of detecting ultra-faint streaks with surface brightnesses approximately an order of magnitude fainter than the pixel level noise. Our maximum likelihood detection method is a model based approach that requires no a priori knowledge about the streak location, orientation, length, or surface brightness. This method enables discovery of typically undiscovered objects, and enables the utilization of low-cost sensors (i.e., higher-noise data). The method also easily facilitates multi-epoch co-addition. We will present the results from the application of this method to simulations, as well as real low earth orbit observations. △ Less

Submitted 22 September, 2016; originally announced September 2016.

Comments: 11 pages, 7 figures, contribution to the Advanced Maui Optical and Space Surveillance Technologies Conference 2016

Report number: LLNL-CONF-703048

Synthesis of Disparate Optical Imaging Data for Space Domain Awareness

Authors: Michael D. Schneider, William A. Dawson

Abstract: We present a Bayesian algorithm to combine optical imaging of unresolved objects from distinct epochs and observation platforms for orbit determination and tracking. By propagating the non-Gaussian uncertainties we are able to optimally combine imaging of arbitrary signal-to-noise ratios, allowing the integration of data from low-cost sensors. Our Bayesian approach to image characterization also a… ▽ More We present a Bayesian algorithm to combine optical imaging of unresolved objects from distinct epochs and observation platforms for orbit determination and tracking. By propagating the non-Gaussian uncertainties we are able to optimally combine imaging of arbitrary signal-to-noise ratios, allowing the integration of data from low-cost sensors. Our Bayesian approach to image characterization also allows large compression of imaging data without loss of statistical information. With a computationally efficient algorithm to combine multiple observation epochs and multiple telescopes, we show statistically optimal orbit inferences. △ Less

Submitted 22 September, 2016; originally announced September 2016.

Comments: 8 pages, 6 figures, contribution to Advanced Maui Optical and Space Surveillance Technologies Conference 2016

Report number: LLNL-CONF-836209

Status of head-on beam-beam compensation in RHIC

Authors: W. Fischer, Z. Altinbas, M. Anerella, M. Blaskiewicz, D. Bruno, M. Costanzo, W. C. Dawson, D. M. Gassner, X. Gu, R. C. Gupta, K. Hamdi, J. Hock, L. T. Hoff, R. Hulsart, A. K. Jain, R. Lambiase, Y. Luo, M. Mapes, A. Marone, R. Michnoff, T. A. Miller, M. Minty, C. Montag, J. Muratore, S. Nemesure , et al. (12 additional authors not shown)

Abstract: In polarized proton operation, the performance of the Relativistic Heavy Ion Collider (RHIC) is limited by the head-on beam-beam effect. To overcome this limitation, two electron lenses are under commissioning. We give an overview of head-on beam-beam compensation in general and in the specific design for RHIC, which is based on electron lenses. The status of installation and commissioning are pre… ▽ More In polarized proton operation, the performance of the Relativistic Heavy Ion Collider (RHIC) is limited by the head-on beam-beam effect. To overcome this limitation, two electron lenses are under commissioning. We give an overview of head-on beam-beam compensation in general and in the specific design for RHIC, which is based on electron lenses. The status of installation and commissioning are presented along with plans for the future. △ Less

Submitted 20 October, 2014; originally announced October 2014.

Comments: 12 pages, contribution to the ICFA Mini-Workshop on Beam-Beam Effects in Hadron Colliders, CERN, Geneva, Switzerland, 18-22 Mar 2013

Journal ref: CERN Yellow Report CERN-2014-004, pp.109-120

A Zero-Gravity Instrument to Study Low Velocity Collisions of Fragile Particles at Low Temperatures

Authors: D. M. Salter, D. Heißelmann, G. Chaparro, G. van der Wolk, P. Reißaus, A. G. Borst, R. W. Dawson, E. de Kuyper, G. Drinkwater, K. Gebauer, M. Hutcheon, H. Linnartz, F. J. Molster, B. Stoll, P. C. van der Tuijn, H. J. Fraser, J. Blum

Abstract: We discuss the design, operation, and performance of a vacuum setup constructed for use in zero (or reduced) gravity conditions to initiate collisions of fragile millimeter-sized particles at low velocity and temperature. Such particles are typically found in many astronomical settings and in regions of planet formation. The instrument has participated in four parabolic flight campaigns to date,… ▽ More We discuss the design, operation, and performance of a vacuum setup constructed for use in zero (or reduced) gravity conditions to initiate collisions of fragile millimeter-sized particles at low velocity and temperature. Such particles are typically found in many astronomical settings and in regions of planet formation. The instrument has participated in four parabolic flight campaigns to date, operating for a total of 2.4 hours in reduced gravity conditions and successfully recording over 300 separate collisions of loosely packed dust aggregates and ice samples. The imparted particle velocities achieved range from 0.03-0.28 m s^-1 and a high-speed, high-resolution camera captures the events at 107 frames per second from two viewing angles separated by either 48.8 or 60.0 degrees. The particles can be stored inside the experiment vacuum chamber at temperatures of 80-300 K for several uninterrupted hours using a built-in thermal accumulation system. The copper structure allows cooling down to cryogenic temperatures before commencement of the experiments. Throughout the parabolic flight campaigns, add-ons and modifications have been made, illustrating the instrument flexibility in the study of small particle collisions. △ Less

Submitted 22 June, 2009; originally announced June 2009.

Comments: D. M. Salter, D. Heißelmann, G. Chaparro, G. van der Wolk, P. Reißaus, A. G. Borst, R. W. Dawson, E. de Kuyper, G. Drinkwater, K. Gebauer, M. Hutcheon, H. Linnartz, F. J. Molster, B. Stoll, P. C. van der Tuijn, H. J. Fraser, and J. Blum