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Development of a software safety process and a case study of its use

The goal of this research is to continue the development of a comprehensive approach to software safety and to evaluate the approach with a case study. The case study is a major part of the project, and it involves the analysis of a specific safety-critical system from the medical equipment domain. The particular application being used was selected because of the availability of a suitable candidate system. We consider the results to be generally applicable and in no way particularly limited by the domain. The research is concentrating on issues raised by the specification and verification phases of the software lifecycle since they are central to our previously-developed rigorous definitions of software safety. The theoretical research is based on our framework of definitions for software safety. In the area of specification, the main topics being investigated are the development of techniques for building system fault trees that correctly incorporate software issues and the development of rigorous techniques for the preparation of software safety specifications. The research results are documented. Another area of theoretical investigation is the development of verification methods tailored to the characteristics of safety requirements. Verification of the correct implementation of the safety specification is central to the goal of establishing safe software. The empirical component of this research is focusing on a case study in order to provide detailed characterizations of the issues as they appear in practice, and to provide a testbed for the evaluation of various existing and new theoretical results, tools, and techniques. The Magnetic Stereotaxis System is summarized.

Knight, John C.↗

Ultrasensitive Sub-monolayer Palladium Induced Chirality Switching and Topological Evolution of Skyrmions

Chiral spin textures are fundamentally interesting, with promise for device applications. Stabilizing chirality is conventionally achieved by introducing Dzyaloshinskii-Moriya interaction (DMI) in asymmetric multilayers, where the thickness of each layer is at least a few monolayers. Here we report an ultrasensitive chirality switching in (Ni/Co) n multilayer induced by capping with only 0.22 monolayer of Pd. Using spin-polarized low-energy electron microscopy, we monitor the gradual evolution of domain walls from left-handed to right-handed Néel walls and quantify the DMI induced by the Pd capping layer. We also observe the chiral evolution of a skyrmion during the DMI switching, where no significant topological protection is found as the skyrmion winding number varies. This corresponds to a minimum energy cost of <1 attojoule during the skyrmion chirality switching. Here, our results demonstrate the detailed chirality evolution within skyrmions during the DMI sign switching, which is relevant to practical applications of skyrmionic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗

A continuous metal-insulator transition driven by spin correlations

While Mott insulators induced by Coulomb interactions are a well-recognized class of metal-insulator transitions, insulators purely driven by spin correlations are much less common, as the reduced energy scale often invites competition from other degrees of freedom. Here, we demonstrate a clean example of a spin-correlation-driven metal-insulator transition in the all-in-all-out pyrochlore antiferromagnet Cd 2 Os 2 O 7 , where the lattice symmetry is preserved by the antiferromagnetism. After the antisymmetric linear magnetoresistance from conductive, ferromagnetic domain walls is removed experimentally, the bulk Hall coefficient reveals four Fermi surfaces of both electron and hole types, sequentially departing the Fermi level with decreasing temperature below the Néel temperature, T N = 227 K. In Cd 2 Os 2 O 7 , the charge gap of a continuous metal-insulator transition opens only at T ~ 10 K << T N . The insulating mechanism parallels the Slater picture, but without a folded Brillouin zone, and contrasts sharply with Mott insulators and spin density waves, where the electronic gap opens above and at T N , respectively.

36 MATERIALS SCIENCE↗

VAN-DAMME: GPU-accelerated and symmetry-assisted quantum optimal control of multi-qubit systems

We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains.

97 MATHEMATICS AND COMPUTING↗

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗

Experimental Study of the 3 He and Neutron Spin Structure at Low Q 2 and The Upgrade of the JLab Polarized 3 He Target

In the scattering process off a nuclear or nucleon target, the Gerasimov-Drell-Hearn (GDH) sum rule for real photons (Q 2 =0 where Q 2 &equiv; -q 2 with q the photon's 4-momentum) relates static properties of the target particle's ground state to dynamic properties of all its excited states. On the other side of the Q 2 spectrum, the Bjorken sum rule holds in the Bjorken limit Q 2 &rarr; &infin;. Bjorken sum rule relates the final structure functions of the proton and neutron to the nucleon axial coupling constant in weak decay. These two sum rules belong to domains where calculations are achievable but use different degrees of freedom: hadronic degrees of freedom at low Q 2 versus partonic degrees of freedom at intermediate Q 2 . Meanwhile, different methods have been used to connect the two sum rules at finite Q 2 values: Chiral Perturbation Theory is used to expand the GDH sum rule while Operator Product Expansion is used to expand the Bjorken sum rule. In recent decades, improvements in polarized beam and polarized target techniques have made it possible to test theoretical predictions in the intermediate Q 2 region. During the Jefferson Lab (JLab) Hall A E97110 experiment, a precise measurement of polarized cross sections was performed at 0.02 < Q 2 < 0.3 GeV 2 using a polarized 3 He target as an effective polarized neutron target. The measured data allowed us to test predictions of Chiral Perturbation Theory at very low Q 2 . Furthermore, an extrapolation to the real photon point Q 2 =0 tests the GDH sum rule on the neutron. In order to reach the small angles necessary for the low Q 2 range, a new septum magnet was installed in Hall A for this experiment. Unfortunately, the magnet was mis-wired during initial running. There were therefore two periods for this experiment: the first period had the defective magnet due to mis-wiring; while in the second period, the magnet had been fixed and was working properly. The cross sections and the asymmetries for the first period must be extracted using a difficult and unusual method employing focal plane variables in the spectrometer. In the work described in this thesis, the target-plane and focal-plane method will be established first and confirmed by elastic scattering cross section measurements from carbon foil and 3 He targets. Cross sections and asymmetries of inelastic scattering were then extracted using the same method, which constitute the main physics results of this thesis. Preliminary results on ITT , the integral of the polarized cross section, were also extracted and are presented in this thesis. In addition to the data analysis of E97110, this thesis includes instrumentation work performed on the polarized 3 He target at JLab. For the 12 GeV program of JLab, the polarized 3 He target is being upgraded to satisfy new experimental requirements. The new target is a convection-based cell with two transfer tubes rather than a single transfer tube as in the former 6 GeV design. The first stage of the target upgrade aims to produce a 40 cm long, 10 amg target that can withstand 30 &mu;A of electron beam current with an in-beam polarization of 55%, doubling the figure-of-merit from the 6 GeV time. Several studies were conducted at the Test Lab of JLab on the new convection cell. Work and improvement done on the Pulse Nuclear Magnetic Resonance (NMR) polarimetry and its test results will be presented. As this thesis is written, the target is being installed in Hall C of JLab in preparation for a 6-month long running from November 2019 to May 2020.

Ton, Nguyen↗

Solution structure of the N-terminal domain of proteasome lid subunit Rpn5

The 26S proteasome is the major protein degradation machinery in living cells. The Rpn5 protein is one scaffolding subunit in the lid subcomplex of the 19S regulatory particle in the proteasome holoenzyme. Herein we report the solution structure of the N-terminal domain (NTD) of yeast Rpn5 at high resolution by NMR spectroscopy. The results show that Rpn5 NTD adopts α-solenoid-like fold in right-handed superhelical configuration formed by a number of α-helices. Structural comparisons with currently available cryo-EM structures reveal local structural differences in the first three helices between yeast and human Rpn5. The results further highlight the conformational flexibility in three possible protein interaction sites. Moreover, the structures of the NTD show large variations among different PCI-containing Rpn subunits. Our current results provide atomic-level structural basis for further investigations of protein-protein interactions and the proteasome assembly pathway.

60 APPLIED LIFE SCIENCES↗

Understanding Lithium Local Environments in LiMn 0.5 Ni 0.5 O 2 Cathodes: A DFT-Supported 6 Li Solid-State NMR Study

LiMn 0.5 Ni 0.5 O 2 has been plagued by the structural failure driven by the irreversible phase change upon subsequent cycling and the structural degradation caused by the seemingly unavoidable Li/Ni exchange. This begs for a better understanding of the correlation between lithium local structures, synthesis conditions, and overall electrochemical properties of materials. In this study, we use density functional theory (DFT) to assist experimental 6 Li solid-state magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy to understand the nature and change in lithium local structures with extended annealing times (168 vs 15 h) synthesized at 900 °C. To correlate the NMR peak changes after different synthesis conditions, we calculated the NMR spectra of representative low-energy model configurations of LiMn 0.5 Ni 0.5 O 2 composition–zigzag, row, and flower structures–as well as the influence of Ni/Mn ordering and Li/Ni exchange on each spectrum using a supercell that is large enough to allow us to consider the effect of different relative configurations of adjacent transition metal (TM) layers. The analysis based on a combination of the calculated NMR and the experimental spectra suggests that most configurations contributing to the experimental spectra are in fact composed of a blend of configurations higher in energy than the classical well-ordered ground-state structures. Further, the extended annealing of LiMn 0.5 Ni 0.5 O 2 slightly enhances Ni/Mn and Li/Mn orderings while reducing the Li/Ni mixing ratio. This study shows how DFT calculations are crucial in providing a better understanding of the experimental characterization data and therefore local environments and domain structures in oxide materials, such as Li-ion battery cathodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spin-orbit coupling induced demagnetization in Ni: Ab initio nonadiabatic molecular dynamics perspective

Spin-orbit coupling (SOC), which can induce spin flip during the relaxation of photoexcited charge carrier, plays a crucial role in spin dynamics. Here in this work, we have used time-domain ab initio nonadiabatic molecular dynamics (NAMD) method to study the SOC induced ultrafast demagnetization in Ni at 300K. The spin-diabatic representation using spin-polarized Kohn-Sham (KS) basis sets and spin-adiabatic representation using spinor basis sets have been applied, and both of them achieve demagnetization in Ni with a timescale around 100fs. The spin-diabatic representation suggests a picture that the electron-phonon coupling (EPC) provides direct energy relaxation channel among the same-spin states, while the SOC can induce spin flip. After photoexcitation, it is found the spin-minority electrons relax to the same-spin states rather than the opposite-spin states, since EPC is larger than SOC by one order of magnitude. By contrast, for the spin-majority electrons, spin flip occurs since there are no empty same-spin states as electron acceptor above the Fermi level. The different relaxation pathways for spin-majority and spin-minority electrons induce the demagnetization. The spin-adiabatic representation provides an Elliott-Yafet spin-phonon scattering picture. The SOC induced reduction of magnetic moment in Ni may induce magnon to drive further demagnetization. The ab initio NAMD simulation provides a critical angle to understand how the SOC and EPC affect demagnetization process in Ni.

36 MATERIALS SCIENCE↗

Modes of Disorder in Poly(carbon monofluoride)

Poly(carbon monofluoride), or (CF) n , is a layered fluorinated graphite material consisting of nanosized platelets. In this work, we present experimental multidimensional solid-state NMR spectra of (CF)n, supported by density functional theory (DFT) calculations of NMR parameters, which overhauls our understanding of structure and bonding in the material by elucidating many ways in which disorder manifests. We observe strong 19 F NMR signals conventionally assigned to elongated or “semi-ionic” C–F bonds and find that these signals are in fact due to domains where the framework locally adopts boat-like cyclohexane conformations. We calculate that C–F bonds are weakened but are not elongated by this conformational disorder. Exchange NMR suggests that conformational disorder avoids platelet edges. We also use a new J-resolved NMR method for disordered solids which provides molecular-level resolution of highly fluorinated edge states. Strings of consecutive difluoromethylene groups at edges are relatively mobile. Topologically distinct edge features, including zigzag edges, crenellated edges, and coves are resolved in our samples by solid-state NMR. Disorder should be controllable in a manner dependent on synthesis, affording new opportunities for tuning the properties of graphite fluorides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences

Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled, which creates barriers to their use in supervised machine learning. We develop a weakly supervised deep learning model for classification of aortic valve malformations using up to 4,000 unlabeled cardiac MRI sequences. Instead of requiring highly curated training data, weak supervision relies on noisy heuristics defined by domain experts to programmatically generate large-scale, imperfect training labels. For aortic valve classification, models trained with imperfect labels substantially outperform a supervised model trained on hand-labeled MRIs. In an orthogonal validation experiment using health outcomes data, our model identifies individuals with a 1.8-fold increase in risk of a major adverse cardiac event. This work formalizes a deep learning baseline for aortic valve classification and outlines a general strategy for using weak supervision to train machine learning models using unlabeled medical images at scale.

60 APPLIED LIFE SCIENCES↗

Effect of chemical substituents attached to the zwitterion cation on dielectric constant

Materials with high dielectric constant, ε s , are desirable in a wide range of applications including energy storage and actuators. Recently, zwitterionic liquids have been reported to have the largest ε s of any liquid and, thus, have the potential to replace inorganic fillers to modulate the material ε s . Although the large ε s for zwitterionic liquids is attributed to their large molecular dipole, the role of chemical substituents attached to the zwitterion cation on ε s is not fully understood, which is necessary to enhance the performance of soft energy materials. Here, we report the impact of zwitterionic liquid cation chemical substituents on ε s (50 < ε s < 300 at room temperature). Dielectric relaxation spectroscopy reveals that molecular reorientation is the main contributor to the high ε s . The low Kirkwood factor g calculated for zwitterionic liquids (e.g., 0.1–0.2) suggests the tendency for the antiparallel zwitterion dipole alignment expected from the strong electrostatic intermolecular interactions. With octyl cation substituents, the g is decreased due to the formation of hydrophobic-rich domains that restrict molecular reorientation under applied electric fields. In contrast, when zwitterion cations are functionalized with ethylene oxide (EO) segments, g increases due to the EO segments interacting with the cations, allowing more zwitterion rotation in response to the applied field. The reported results suggest that high ε s zwitterionic liquids require a large molecular dipole, compositionally homogeneous liquids (e.g., no aggregation), a maximized zwitterion number density, and a high g, which is achievable by incorporating polar chemical substituents onto the zwitterion cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synergy of two lower hybrid waves with different frequencies on EAST

Lower hybrid current drive (LHCD) is one of the major approaches maintaining long pulse discharges on EAST. There are two lower hybrid (LH) systems on EAST launching waves at 4.6 GHz and 2.45 GHz into the plasma, respectively, and the input power of the 4.6 GHz wave is typically dominant. Here, the synergy of the two waves and the modification of the power deposition of the 4.6 GHz wave by coupling the 2.45 GHz wave are investigated theoretically. According to the phase space analysis, the wave propagation domains of the two LH waves always overlap substantially with each other for typical LHCD experimental parameters on EAST, indicating that the coupling between them might be strong. Ray-tracing/Fokker-Planck simulations for a LH current drive experiment on EAST show that the change of the power deposition profile due to the coupling could be understood by the rise and fall of the tails of the parallel electron distribution functions on different flux surfaces. If either the injected wave power at 2.45 GHz is comparable with that at 4.6 GHz or the incident N ∥ of the 2.45 GHz wave reaches a high value (e.g., $5.7/\sqrt{T_{e,0}}$), the power deposition profile of the 4.6 GHz wave can be modified greatly due to the coupling with the 2.45 GHz wave. With the parameters compatible with the ability of the LH wave system on EAST, injection of the 2.45 GHz wave can still modify the power deposition profile of the 4.6 GHz wave significantly by combining those two approaches. Finally, it is shown how a 4.6 GHz wave which cannot be Landau damped when injected alone is absorbed in low density plasmas with a magnetic shear reversal configuration in the presence of a 2.45 GHz wave.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SOHO-Ulysses Coordinated Studies During the Two Extended Quadratures and the Alignment of 2007-2008

During SOHO-Sun-Ulysses quadratures the geometry of the configuration makes it possible to sample "in situ" the plasma parcels that are remotely observed in the corona. Although the quadrature position occurs at a well defined instant in time, we typically take data while Ulysses is within +/- 5 degrees of the limb, with the understanding that plasma sampled by Ulysses over this time interval can all be traced to its source in the corona. The relative positions of SOHO and Ulysses in winter 2007 (19 Dec 2006-28 May 2007) are unusual: the SOHO-Sun-Ulysses included angle is always between 85 and 95 degrees - the quadrature lasts for 5 months! This provides an opportunity for extended observations of specific observing objectives. In addition, in summer 2007, Ulysses (at 1.34 AU) is in near-radial alignment with Earth/ACE/Wind and SOHO, allowing us to analyze radial gradients and propagation in the solar wind and inner heliosphere. Our own quadrature campaigns rely heavily on LASCO and UVCS coronal observations: LASCO giving the overall context above 2 solar radii while the UVCS spectrograph acquired data from - 1.5 to, typically, 4-5 solar radii. In the past, coronal parameters have been derived from data acquired by these two experiments and compared with "in situ" data of Ulysses' SWOOPS and SWICS. Data from other experiments like EIT, CDS, SUMER, Sac Peak Fe XIV maps, magnetic field maps from the Wilcox solar magnetograph, MLSO, from MDI, and from the Ulysses magnetograph experiment have been, and will be, used to complement LASCO/UVCS/SWOOPS and SWICS data. We anticipate that observations by ACE/WIND/STEREO/Hinode and other missions will be relevant as well. During the IHY campaigns, Ulysses will be 52-80 degrees south in winter 2007, near sunspot minimum. Hence, our own scientific objective will be to sample high speed wind or regions of transition between slow and fast wind. This might be a very interesting situation - not met in previous quadratures - allowing us to study the variation of element abundances across streamer borders in the corona and,correspondingly, "in situ". Also, observing plasma over prolonged time intervals and at different latitudes, we may examine the latitude variation of the fractionation effect (e.g. Yon Steiger, 2002) and its dependence on time (e.g. Woo, 2004). For instance, if the FIP bias is dictated by the duration of plasma confinement in solar loops, its value in streamers should depend on the streamer age. Analogous variations should be found in the abundances of "in situ" plasma released by the streamer. All Ulysses and SOHO data is in the public domain and accessible so different objectives could be addressed by others. The winter 2008 quadrature will be well into the next sunspot cycle and there might be significant high mid-latitude activity. Ulysses will be up to 80 degrees in the northern hemisphere at this time and able to detect the resulting ICMEs and ejecta, allowing us to study the physical parameters of the propagating CME bubble/core/front, and/or to study the coronal and "in situ" characteristics of the current sheet associated with the event (e.g. Bemporad et al. 2005), so far still vaguely defined.

Suess, S. T.↗

Hubble Space Telescope Magnetometer and Two-Gyro Control Law Design, Implementation, and On-Orbit Performance

For f i h years, the science mission of the Hubble Space Telescope (HST) required using at least three of six rate gyros for attitude control. In the past, HST has mitigated gyro hardware failures by replacement of the failed units through Space Shuttle Servicing Missions. Following the tragic loss of Space Shuttle Columbia on STS-107, the desire to have a safe haven for astronauts during missions has resulted in the cancellation of all planned maxu14 missions to HST. While a robotic servicing mission is being currently being planned, controlling with alternate sensors to replace failed gyros can extend the HST Science mission until the robotic mission can be performed and extend science at HST s end of life. A two-gym control law has been designed and implemented using magnetometers (Magnetic Sensing System - MSS), fixed head star trackers (FHSTs), and Fine Guidance Sensors (FGSs) to control vehicle rate about the missing gyro axis. The three aforementioned sensors are used in succession to reduce HST boresight jitter to less than 7 milli-arcseconds rms and attitude error to less than 10 milli-arcseconds prior to science imaging. The MSS and 2-Gyro (M2G) control law is used for large angle maneuvers and attitude control during earth occultation of FHSTs and FGSs. The Tracker and 2-Gyro (T2G) control law dampens M2G rates and corrects the majority of attitude error in preparation for guide star acquisition with the FGSs. The Fine Guidance Sensor and 2-Gyro (F2G) control law d a m p T2G rates and controls HST attitude during science imaging. This paper describes the M2G control law. Details of M2G algorithms are presented, including computation of the HST 3-axis attitude error estimate, design of the M2G control law, SISO hear stability analyses, and restrictions on operations to maintain the h d t h and safety requirement of a 10degree maximum attitude error. Results of simulations performed in HSTSIM, a high-fidelity non-linear time domain simulation, are presented to predict HST on-orbit performance in attitude hold and maneuver modes. Simulation results are compared to on-orbit data from M2G flight tests performed in November and December 2004 and February 2005. Flight telemetry, using a currently available third gyro, shows that HST attitude error with the new M2G control law is maintained below the 10-degree requirement, and attitude errors are under 2 degrees for 95% of the time.

Wirzburger, John H.↗