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At least 91 records · Page 5

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception: Preprint

This paper puts forth a system architecture for an infrastructure-based cooperative perception (CP) fusion engine, to provide a complete state-space digital representation, with measurable accuracy, to support a wide-range of applications. The architecture includes the inputs, functional flow, data standardization recommendations, outputs and supported applications. The CP engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure (IRI), that complements and accelerates connected and automated vehicle (CAV) technology. that the CP acquires and fuses information from sensors (radar, LiDAR, and cameras), and CAVs to intelligently perceive roadway traffic states of all moving objects, create a complete three-dimensional digital representation of that state-space, and communicate it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications for CAVs as examples. The IRI approach, as opposed to a vehicle centric approach, is found to be more scalable in that it can deployed to the roughly 300,000 signalized intersections more readily than the over 300 million vehicles in the US, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and GHG reduction.

ADVANCED PROPULSION SYSTEMS↗

Systems and methods of adaptive two-wavelength single-camera imaging thermography (ATSIT) for accurate and smart in-situ process temperature measurement during metal additive manufacturing

A two-wavelength, single-camera imaging thermography system for in-situ temperature measurement of a target, comprising: a target light path inlet conduit for receiving a target light beam reflected from the target; a beam splitter installed in a splitter housing at a distal end of the target light path conduit, wherein the beam splitter divides the target light beam into a first light beam and a second light beam; a first light path conduit emanating from the splitter housing comprising a first aperture iris installed within the first light path conduit for aligning the first light beam; a first band pass filter installed within the first light path conduit for regulating the first light beam to a first wavelength λ1 and an optional half waveplate installed within the first light path conduit to modulate a polarization ratio of the first light beam of λ1 wavelength; a second light path conduit emanating from the splitter housing comprising a second aperture iris installed within the second light path conduit for aligning the second light beam; a second band pass filter installed within the second light path conduit for regulating the second light beam to a second wavelength λ2; a junction housing, wherein distal ends of each of the first and second light path conduits are connected to the junction housing; a polarizing beam splitter installed in the junction housing, wherein the polarizing beam splitter reflects the first light beam of λ1 wavelength along the same path or a parallel path of the second light beam of λ2 wavelength that passes directly through the polarizing beam splitter unreflected to create a merged light beam comprising light of λ1 and λ2 wavelengths; and a light path outlet conduit connected to the junction for directing the merged beam to a high-speed camera for imaging.

Zhao, Xiayun↗

The 200 Gbps Challenge: Imagining HL-LHC analysis facilities

The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-LHC computing challenges with new approaches and paradigms, driven by our vision of what HL-LHC analysis will require. The institute uses a "Grand Challenge" format, constructing a series of increasingly large, complex, and realistic exercises to show the vision of HL-LHC analysis. Recently, the focus has been demonstrating the IRIS-HEP analysis infrastructure at scale and evaluating technology readiness for production. As a part of the Analysis Grand Challenge activities, the institute executed a "200 Gbps Challenge", aiming to show sustained data rates into the event processing of multiple analysis pipelines. The challenge integrated teams internal and external to the institute, including operations and facilities, analysis software tools, innovative data delivery and management services, and scalable analysis infrastructure. The challenge showcases the prototypes - including software, services, and facilities - built to process around 200 TB of data in both the CMS NanoAOD and ATLAS PHYSLITE data formats with test pipelines. The teams were able to sustain the 200 Gbps target across multiple pipelines. The pipelines focusing on event rate were able to process at over 30 MHz. These target rates are demanding; the activity revealed considerations for future testing at this scale and changes necessary for physicists to work at this scale in the future. The 200 Gbps Challenge has established a baseline on today's facilities, setting the stage for the next exercise at twice the scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

A novel approach to RF power coupling in Radio-Frequency Quadrupole (RFQ) structures: built-in coaxial double-loop coupling port

Efficient and reliable RF power couplers in accelerating cavities require precise impedance matching and mechanical stability to ensure optimal beam energy transfer. In radio-frequency quadrupole (RFQ) accelerators, power is commonly delivered using waveguide iris or coaxial loop couplers. Iris couplers can handle high RF power but lack tunability, while coaxial loop couplers offer tuning flexibility but are limited in power handling and thermal performance. We propose a new RFQ power coupling concept utilizing a single input coaxial center-fed double-loop antenna built into a vane in an RFQ structure . The design integrates back-to-back loops into the RFQ vanes, fed by a TEM coaxial transmission line with standard 50-Ω characteristic impedance. The configuration can allow straightforward and easy ceramic window replacement without retuning, and coupling strength is adjusted with protruding tuning rods. Numerical simulations, performed with both a simplified RFQ model and the Spallation Neutron Source RFQ, demonstrate improved RF performance and reduced dipole mode excitation. The results establish the coaxial double-loop coupler as a practical alternative for high-power RFQ coupling applications.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗

ExaFEL: extreme-scale real-time data processing for X-ray free electron laser science

ExaFEL is an HPC-capable X-ray Free Electron Laser (XFEL) data analysis software suite for both Serial Femtosecond Crystallography (SFX) and Single Particle Imaging (SPI) developed in collaboration with the Linac Coherent Lightsource (LCLS), Lawrence Berkeley National Laboratory (LBNL) and Los Alamos National Laboratory. ExaFEL supports real-time data analysis via a cross-facility workflow spanning LCLS and HPC centers such as NERSC and OLCF. Our work therefore constitutes initial path-finding for the US Department of Energy's (DOE) Integrated Research Infrastructure (IRI) program. We present the ExaFEL team's 7 years of experience in developing real-time XFEL data analysis software for the DOE's exascale supercomputers. We present our experiences and lessons learned with the Perlmutter and Frontier supercomputers. Furthermore we outline essential data center services (and the implications for institutional policy) required for real-time data analysis. Finally we summarize our software and performance engineering approaches and our experiences with NERSC's Perlmutter and OLCF's Frontier systems. This work is intended to be a practical blueprint for similar efforts in integrating exascale compute resources into other cross-facility workflows.

59 BASIC BIOLOGICAL SCIENCES↗

Absolute Cavity Pyrgeometer (ACP)

ACP Measures atmospheric longwave irradiance with traceability to the International System of Units (SI). To date the Interim world reference World Infrared Standard Group (WISG) is traceable to blackbody (not sky/atmosphere), and InfraRed Integrating Sphere (IRIS) Developed by the World Radiation Center (PMOD) is traceable to blackbody irradiance. The ACP is self calibrated radiometer using heat substitution like Absolute Cavity Radiometer (ACR) that is self calibrated radiometer using electrical substitution to measure solar irradiance. ACP is a contribution to develop the world reference with traceability to SI, using the outdoor irradiance as the source, instead of blackbody.

ACP↗

Absolute Cavity Pyrgeometer (ACP)

Measure atmospheric longwave irradiance. ABSOLUTE measurement traceable to International System of Units (SI). To date, Interim world reference traceable to blackbody (not sky/atmosphere), World Infrared Standard Group (WISG). InfraRed Integrating Sphere (IRIS) Developed by the World Radiation Center (PMOD) is traceable to blackbody irradiance. ACP is self-calibrated radiometer using heat substitution like Absolute Cavity Radiometer (ACR) that is self-calibrated radiometer using electrical substitution to measure solar irradiance. ACP is a contribution to develop the world reference with traceability to SI, using the outdoor irradiance as the source, instead of blackbody.

ACP↗

Balanced k -means clustering on an adiabatic quantum computer

Adiabatic quantum computers are a promising platform for efficiently solving challenging optimization problems. Therefore, many are interested in using these computers to train computationally expensive machine learning models. We present a quantum approach to solving the balanced k-means clustering training problem on the D-Wave 2000Q adiabatic quantum computer. In order to do this, we formulate the training problem as a quadratic unconstrained binary optimization (QUBO) problem. Unlike existing classical algorithms, our QUBO formulation targets the global solution to the balanced k-means model. We test our approach on a number of small problems and observe that despite the theoretical benefits of the QUBO formulation, the clustering solution obtained by a modern quantum computer is usually inferior to the solution obtained by the best classical clustering algorithms. Nevertheless, the solutions provided by the quantum computer do exhibit some promising characteristics. We also perform a scalability study to estimate the run time of our approach on large problems using future quantum hardware. Finally, as a final proof of concept, we used the quantum approach to cluster random subsets of the Iris benchmark data set.

97 MATHEMATICS AND COMPUTING↗

Adiabatic quantum support vector machines

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic quantum approach for training support vector machines. We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach. Next, we compare the test accuracy of our quantum approach against a classical approach that uses the Scikit-learn library in Python across five benchmark datasets (Iris, Wisconsin Breast Cancer (WBC), Wine, Digits, and Lambeq). We show that our quantum approach obtains accuracies on par with the classical approach. Finally, we perform a scalability study in which we compute the total training times of the quantum approach and the classical approach with an increasing number of features and an increasing number of data points in the training dataset. In conclusion, our scalability results show that the quantum approach obtains a 3.5–4.5x speedup over the classical approach on datasets with many (millions of) features.

Computational Complexity↗

Triple oxygen and hydrogen stable isotope composition of hydroxyl water in Orgueil (CI-type) and Tagish Lake (C2-type) carbonaceous chondrites

The primitive carbonaceous chondrites are of interest to cosmochemical science because they contain relatively large amounts of ‘water’ (H 2 O and/or OH – ) within phyllosilicate minerals. This water is evidence for the accretion of ices by their parent planetesimals, and thus represents an archive of the isotopic compositions of H 2 O in the protoplanetary environments. Here, in this study, we used thermogravimetry-enabled laser spectroscopy (TGA-IRIS) analyses of the Orgueil and Tagish Lake meteorites to make δ 2 H, δ 18 O, and Δ′ 17 O measurements of the H 2 O and OH – contained in the different hydrous minerals that comprise each meteorite. In Orgueil, we measured mass-weighted averages of OH – in the saponite and serpentine phyllosilicate matrix to be δ 2 H = 192 ‰, δ 18 O = 1.5 ‰, which are unquestionably of extraterrestrial origin with Δ′ 17 O = 1.0 ‰. For Tagish Lake, analogous values of OH– in the saponite and serpentine phyllosilicate matrix are δ 2 H = 704 ‰, δ 18 O = 11.3 ‰, and are similarly unambiguously extraterrestrial with Δ′ 17 O = 0.82 ‰. We estimate that the parent H 2 O involved in aqueous alteration of Orgueil had δ 18 O value ≥ +23 ‰. In Orgueil, we interpret the phyllosilicate petrographic relationships, and the δ 18 O values of OH – in saponite and serpentine to indicate that saponite formed first, at a lower temperature by 35 to 53 °C than serpentine. This suggests that the Orgueil parent body experienced increasing temperature during the phase of active aqueous alteration (prograde) which set the δ 18 O OH values of the serpentine and saponite. In the case of Tagish Lake, serpentine formed at a lower temperature by 32 to 60 °C than saponite, for the simplest case with constant δ 18 O H2O values. If serpentine formed first, followed by saponite formation at 32 to 60 °C °C higher temperature, this suggests that Tagish Lake sample TL1 underwent prograde aqueous alteration as the parent body heated up. We find evidence that the parent H 2 O for Orgueil, Tagish Lake sample TL1, and Murchison (based on data from a previous study) may have had Δ′ 17 O values of >0.64 ‰.

Aqueous alteration↗

Signature of 0 + excited state and shape coexistence in 94 Kr through 93 Kr(d,p) 94 Kr reaction

A measurement of the excitation spectrum of 94 Kr via one-neutron transfer to the ground state of 93 Kr using the 93 Kr(d,p) 94 Kr reaction at 8A MeV, observing the outgoing protons, performed with the IRIS facility at TRIUMF is reported. Two states in 94 Kr, at 1.50±0.14 MeV and 2.20±0.14 MeV, were observed. An adiabatic-wave approximation analysis of the differential cross sections leads us to identify the lower energy state as being populated with neutron transfer to the 3 s1/2 orbital. This leads to the first observation of the lowest 0 + excited state in 94 Kr, hence signaling shape co-existence. Theoretical calculations performed within the in-medium similarity renormalization group framework are presented that also show the existence of a low-energy 0 + state, aligning qualitatively with the observation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Kelvin Probe Force Microscopy Imaging of Plasticity in Hydrogenated Perovskite Nickelate Multilevel Neuromorphic Devices

Ion drift in nanoscale electronically inhomogeneous semiconductors is among the most important mechanisms being studied for designing neuromorphic computing hardware. However, nondestructive imaging of the ion drift in operando devices directly responsible for multiresistance states and synaptic memory represents a formidable challenge. Here, we present Kelvin probe force microscopy imaging of hydrogen-doped perovskite nickelate device channels subject to high-speed electric field pulses to directly visualize proton distribution by monitoring surface potential changes spatially, which is also supported with finite element-based electric field distribution studies. First-principles calculations provide mechanistic insights into the origin of surface potential changes as a function of hydrogen donor doping that serves as the contrast mechanism. We demonstrate 128 (7-bit) nonvolatile conductance levels in such devices relevant to in-memory computing applications. The synaptic plasticity measurements are implemented in spiking neural networks and show promising results for classification (SciKit Learn’s Iris and Wine data sets) and control (OpenAI’s CartPole-v1 and BipedalWalker-v3) simulation tasks.

Kelvin probe force microscopy↗

Regional Moment Tensor Inversion Using Rotational Observations

There are benefits from the addition of rotational motions to translational displacements for moment tensor (MT) inversions. The rotational radiation pattern is orthogonal to the shear radiation pattern, thus incorporating rotations is equivalent to gaining another observation point on the focal sphere. We demonstrated this by simulating curl and displacement wavefields for a regional distance station. Thus, one 6-C station (3-Component translational + 3-Component rotational) gathers the same information on radiation pattern as two 3-C stations at 90° azimuth from one another along the focal plane axis, which is sometimes difficult to obtain when restricted to surface sensors. We added rotational Green's functions to a regional MT inversion scheme (long-period, time-domain, and linear inversion) by computing spatial gradients from f-κ reflectivity synthetics. For rotational data, we used Array Derived Rotations (ADR) from Piñon Flats Observatory Array and Golay array deployed during IRIS Community Wavefield Demonstration Experiment. The hope is to ultimately use compact and field deployable broadband rotational seismometers instead of ADRs. Rotational motions were predicted from well-constrained deviatoric MT solutions of nine earthquakes recorded by the arrays and other seismic networks. Additionally, we formed three station sparse datasets with (3-C and 6-C) and without rotational ground motions (3-C only) for eight earthquakes testing the benefits of including rotational waveforms in MT inversions when they are equally weighted with translational waveforms. Adding rotational motions improved the double-couple components and reduced compensated-linear-vector-dipole and isotropic components in full-MT solutions using sparse datasets with poor coverage.

58 GEOSCIENCES↗

Dissecting Anvil Cloud Response to Sea Surface Warming

Abstract We derive an anvil cloud diagnostic from the continuity equation of cloud ice and apply it to the output of convection‐permitting Energy Exascale Earth System Model (E3SM) simulations run in radiative‐convective equilibrium mode. This diagnostic shows that anvil cloud fraction can be reliably diagnosed as a product of cloud detrainment and lifetime. Detrainment is found to be approximated well by a product of clear sky convergence and cloud ice mixing ratio, while cloud lifetime is dominated by sedimentation. Taken together, this diagnostic expresses anvil cloud fraction as a function of five physically measurable quantities. Of these, clear‐sky convergence changes drive the anvil cloud reduction with warming while an increase in cloud ice mixing ratio buffers the decrease. Accordingly, this study provides a theoretical foundation upon which the Stability‐Iris hypothesis can be tested.

54 ENVIRONMENTAL SCIENCES↗

Quantum discriminator for binary classification

Abstract Quantum computers have the unique ability to operate relatively quickly in high-dimensional spaces—this is sought to give them a competitive advantage over classical computers. In this work, we propose a novel quantum machine learning model called the Quantum Discriminator, which leverages the ability of quantum computers to operate in the high-dimensional spaces. The quantum discriminator is trained using a quantum-classical hybrid algorithm in $$\mathcal {O}(N\log N)$$ O ( N log N ) time, and inferencing is performed on a universal quantum computer in $$\mathcal {O}(N)$$ O ( N ) time. The quantum discriminator takes as input the binary features extracted from a given datum along with a prediction qubit, and outputs the predicted label. We analyze its performance on the Iris and Bars and Stripes data sets, and show that it can attain 99% accuracy in simulation.

97 MATHEMATICS AND COMPUTING↗

Planck intermediate results

In this work, we describe an extension of the most recent version of the Planck Catalogue of Compact Sources (PCCS2), produced using a new multi-band Bayesian Extraction and Estimation Package (BeeP). BeeP assumes that the compact sources present in PCCS2 at 857 GHz have a dust-like spectral energy distribution (SED), which leads to emission at both lower and higher frequencies, and adjusts the parameters of the source and its SED to fit the emission observed in Planck’s three highest frequency channels at 353, 545, and 857 GHz, as well as the IRIS map at 3000 GHz. In order to reduce confusion regarding diffuse cirrus emission, BeeP’s data model includes a description of the background emission surrounding each source, and it adjusts the confidence in the source parameter extraction based on the statistical properties of the spatial distribution of the background emission. BeeP produces the following three new sets of parameters for each source: (a) fits to a modified blackbody (MBB) thermal emission model of the source; (b) SED-independent source flux densities at each frequency considered; and (c) fits to an MBB model of the background in which the source is embedded. BeeP also calculates, for each source, a reliability parameter, which takes into account confusion due to the surrounding cirrus. This parameter can be used to extract sub-samples of high-frequency sources with statistically well-understood properties. We define a high-reliability subset (BeeP/base), containing 26 083 sources (54.1% of the total PCCS2 catalogue), the majority of which have no information on reliability in the PCCS2. We describe the characteristics of this specific high-quality subset of PCCS2 and its validation against other data sets, specifically for: the sub-sample of PCCS2 located in low-cirrus areas; the Planck Catalogue of Galactic Cold Clumps; the Herschel GAMA15-field catalogue; and the temperature- and spectral-index-reconstructed dust maps obtained with Planck’s Generalized Needlet Internal Linear Combination method. The results of the BeeP extension of PCCS2, which are made publicly available via the Planck Legacy Archive, will enable the study of the thermal properties of well-defined samples of compact Galactic and extragalactic dusty sources.

79 ASTRONOMY AND ASTROPHYSICS↗

High resolution diagnostic tools for superconducting radio frequency cavities

Superconducting radio-frequency (SRF) cavities are one of the fundamental building blocks of modern particle accelerators. To achieve the highest quality factors (10 10 –10 11 ), SRF cavities are operated at liquid helium temperatures. Magnetic flux trapped on the surface of SRF cavities during cool-down below the critical temperature is one of the leading sources of residual RF losses. Instruments capable of detecting the distribution of trapped flux on the cavity surface are in high demand in order to better understand its relation to the cavity material, surface treatments and environmental conditions. We have designed, developed, and commissioned two high-resolution diagnostic tools to measure the distribution of trapped flux at the surface of SRF cavities. One is a magnetic field scanning system, which uses cryogenic Hall probes and anisotropic magnetoresistance sensors that fit the contour of a 1.3 GHz cavity. This setup has a spatial resolution of ~ 13 μm in the azimuthal direction and ~ 1 cm along the cavity contour. The second setup is a stationary, combined magnetic and temperature mapping system, which uses anisotropic magnetoresistance sensors and carbon resistor temperature sensors, covering the surface of a 3 GHz SRF cavity. This system has a spatial resolution of 5 mm close to the iris and 11 mm at the equator. Initial results show a non-uniform distribution of trapped flux on the cavities’ surfaces, dependent on the magnitude of the applied magnetic field during field-cooling below the critical temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗