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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Constraints on a φCDM model from strong gravitational lensing and updated Hubble parameter measurements

We constrain the scalar field dark energy model with an inverse power-law potential, i.e., V(φ) ∝ φ{sup −α} (α > 0), from a set of recent cosmological observations by compiling an updated sample of Hubble parameter measurements including 30 independent data points. Our results show that the constraining power of the updated sample of H(z) data with the HST prior on H{sub 0} is stronger than those of the SCP Union2 and Union2.1 compilations. A recent sample of strong gravitational lensing systems is also adopted to confine the model even though the results are not significant. A joint analysis of the strong gravitational lensing data with the more restrictive updated Hubble parameter measurements and the Type Ia supernovae data from SCP Union2 indicates that the recent observations still can not distinguish whether dark energy is a time-independent cosmological constant or a time-varying dynamical component.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Constraining the time evolution of dark energy, curvature and neutrino properties with cosmic chronometers

We use the latest compilation of observational Hubble parameter measurements estimated with the differential evolution of cosmic chronometers , in the redshift range 0< z <2, to place constraints on cosmological parameters. We used a Markov-Chain Monte-Carlo approach to sample the parameter space for the cosmic chronometers dataset alone and in combination with other state-of-the art cosmological measurements: CMB data from the latest Planck 2015 release, the most recent estimate of the Hubble constant H {sub 0}, a compilation of recent baryon acoustic oscillation data, and the latest type Ia cosmological supernovae sample. From late-Universe probes alone ( z <2) we find that w {sub 0} = −0.9 ± 0.18 and w {sub a} = −0.5 ± 1.7, and when combining also Planck 2015 data we obtain w {sub 0}=−0.98± 0.11 and w {sub a} =−0.30±0.4. These new constraints imply that nearly all quintessence models are disfavoured by the data; only phantom models or a pure cosmological constant are favoured. This is a remarkable finding as it imposes severe constraints on the nature of dark energy. For the curvature our constraints are Ω {sub k} = 0.003 ± 0.003, considering also CMB data. We also find that H ( z ) data from cosmic chronometers are important to constrain parameters that do no affect directly the expansion history, by breaking or reducing degeneracies with other parameters. We find that N {sub eff} = 3.17 ± 0.15, thus excluding the possibility of an extra (sterile) neutrino at more than 5 σ, and put competitive limits on the sum of neutrino masses, Σ m {sub ν}< 0.27 eV at 95% confidence level. Finally, we constrain the redshift evolution of dark energy by exploring separately the early and late-Universe, and find a dark energy equation of state evolution w ( z ) consistent with that in the ΛCDM model at the ± 0.4 level over the entire redshift range 0 < z < 2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Testing ΛCDM at the lowest redshifts with SN Ia and galaxy velocities

Peculiar velocities of objects in the nearby universe are correlated due to the gravitational pull of large-scale structure. By measuring these velocities, we have a unique opportunity to test the cosmological model at the lowest redshifts. We perform this test, using current data to constrain the amplitude of the "signal" covariance matrix describing the velocities and their correlations. We consider a new, well-calibrated "Supercal" set of low-redshift SNe Ia as well as a set of distances derived from the fundamental plane relation of 6dFGS galaxies. Here, analyzing the SN and galaxy data separately, both results are consistent with the peculiar velocity signal of our fiducial ΛCDM model, ruling out the noise-only model with zero peculiar velocities at greater than 7σ (SNe) and 8σ (galaxies). When the two data sets are combined appropriately, the precision of the test increases slightly, resulting in a constraint on the signal amplitude of A = 1.05 -0.21 +0.25 where A = 1 corresponds to our fiducial model. Equivalently, we report an 11% measurement of the product of the growth rate and amplitude of mass fluctuations evaluated at z eff = 0.02, f σ 8 = 0.428 -0.045 +0.048 , valid for our fiducial ΛCDM model. Here, we explore the robustness of the results to a number of conceivable variations in the analysis and find that individual variations shift the preferred signal amplitude by less than ~0.5σ. We briefly discuss our Supercal SN Ia results in comparison with our previous results using the JLA compilation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Low mass X-ray binaries in the Inner Galaxy: implications for millisecond pulsars and the GeV excess

If millisecond pulsars (MSPs) are responsible for the excess gamma-ray emission observed from the region surrounding the Galactic Center, the same region should also contain a large population of low-mass X-ray binaries (LMXBs). In this study, we compile and utilize a sizable catalog of LMXBs observed in the the Milky Way's globular cluster system and in the Inner Galaxy, as well as the gamma-ray emission observed from globular clusters, to estimate the flux of gamma rays predicted from MSPs in the Inner Galaxy. From this comparison, we conclude that only up to ∼ 4-23% of the observed gamma-ray excess is likely to originate from MSPs. This result is consistent with, and more robust than, previous estimates which utilized smaller samples of both globular clusters and LMXBs. If MSPs had been responsible for the entirety of the observed excess, INTEGRAL should have detected ∼ 10{sup 3} LMXBs from within a 10{sup o} radius around the Galactic Center, whereas only 42 LMXBs (and 46 additional LMXB candidates) have been observed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

ROOT 6 and beyond: TObject, C++14 and many cores

Following the release of version 6, ROOT has entered a new area of development. It will leverage the industrial strength compiler library shipping in ROOT 6 and its support of the C++11/14 standard, to significantly simplify and harden ROOT's interfaces and to clarify and substantially improve ROOT's support for multi-threaded environments. Furthermore, this talk will also recap the most important new features and enhancements in ROOT in general, focusing on those allowed by the improved interpreter and better compiler support, including I/O for smart pointers, easier type safe access to the content of TTrees and enhanced multi processor support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

XACC: a system-level software infrastructure for heterogeneous quantum–classical computing

Quantum programming techniques and software have advanced significantly over the past five years, with a majority focusing on high-level language frameworks targeting remote REST library APIs. As quantum computing architectures advance and become more widely available, lower-level, system software infrastructures will be needed to enable tighter, co-processor programming and access models. In this work, we present XACC, a system-level software infrastructure for quantum–classical computing that promotes a service-oriented architecture to expose interfaces for core quantum programming, compilation, and execution tasks. Additionally, we detail XACC's interfaces, their interactions, and its implementation as a hardware-agnostic framework for both near-term and future quantum–classical architectures. We provide concrete examples demonstrating the utility of this framework with paradigmatic tasks. Our approach lays the foundation for the development of compilers, associated runtimes, and low-level system tools tightly integrating quantum and classical workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Shearing approach to gauge-invariant Trotterization

Universal quantum simulations of gauge field theories are exposed to the risk of gauge symmetry violations when it is not known how to compile the desired operations exactly using the available gate set. In this article, we show how time evolution can be compiled in an Abelian gauge theory—if only approximately—without compromising gauge invariance, by graphically motivating a block-diagonalization procedure. When gauge-invariant interactions are associated with a “spatial network” in the space of discrete quantum numbers, it is seen that cyclically shearing the spatial network converts simultaneous updates to many quantum numbers into conditional updates of a single quantum number; ultimately, this eliminates any need to pass through (and acquire overlap onto) unphysical intermediate configurations. Shearing is explicitly applied to gauge-matter and magnetic interactions of lattice quantum electrodynamics. The features that make shearing successful at preserving Abelian gauge symmetry may also be found in non-Abelian theories, bringing one closer to gauge-invariant simulations of quantum chromodynamics.

Gauge theories↗
DOE OSTI2016

Octahedral rotation patterns in strained EuFeO 3 and other Pbnm perovskite films: Implications for hybrid improper ferroelectricity

Here, we report the relationship between epitaxial strain and the crystallographic orientation of the in-phase rotation axis and A -site displacements in Pbnm-type perovskite films. Synchrotron diffraction measurements of EuFeO 3 films under strain states ranging from 2% compressive to 0.9% tensile on cubic or rhombohedral substrates exhibit a combination of a - a + c - and a + a - c - rotational patterns. We compare the EuFeO 3 behavior with previously reported experimental and theoretical work on strained Pbnm-type films on nonorthorhombic substrates, as well as additional measurements from LaGaO 3 , LaFeO 3 , and Eu 0.7 Sr 0.3 MnO 3 films on SrTiO 3 . Compiling the results from various material systems reveals a general strain dependence in which compressive strain strongly favors a - a + c - and a + a - c - rotation patterns and tensile strain weakly favors a - a - c + structures. In contrast, EuFeO 3 films grown on Pbnm-type GdScO 3 under 2.3% tensile strain take on a uniform a - a + c - rotation pattern imprinted from the substrate, despite strain considerations that favor the a - a - c + pattern. Our results point to the use of substrate imprinting as a more robust route than strain for tuning the crystallographic orientations of the octahedral rotations and A -site displacements needed to realize rotation-induced hybrid improper ferroelectricity in oxide heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Current data are consistent with flat spatial hypersurfaces in the Λ CDM cosmological model but favor more lensing than the model predicts

Here, we study the performance of three pairs of tilted, and a pair of untilited, ΛCDM cosmological models, with three of these four pairs allowing for non-flat spatial hypersurfaces, against cosmic microwave background (CMB) temperature and polarization power spectrum data (P18), measurements of the Planck 2018 lensing potential power spectrum (lensing), and a large compilation of non-CMB data (non-CMB). For the eight models, we measure cosmological parameters and study whether or not pairs of the data sets (as well as subsets of them) are mutually consistent in these models. Half of these models allow the lensing consistency parameter A L , which re-scales the gravitational potential power spectrum, to be an additional free parameter to be determined from data, while the other three have A L = 1 which is the theoretically expected value. The pair of untilted non-flat ΛCDM models are incompatible with P18 data. The tilted spatially-flat models assume the usual primordial spatial inhomogeneity power spectrum that is a power law in wave number. The tilted non-flat models assume either the primordial power spectrum used in the Planck group anal yses [Planck P(q)], that has recently been numerically shown to be a good approximation to what is quantum-mechanically generated from a particular choice of closed inflation model initial conditions, or a recently computed power spectrum [new P(q)] that quantum-mechanically follows from a different set of non-flat inflation model initial conditions. In the tilted non-flat models with A L = 1 we find differences between P18 data and non-CMB data cosmological parameter constraints, which are large enough to rule out the Planck P(q) model at 3σ but not the new P(q) model. No significant differences are found when cosmological parameter constraints obtained with two different data sets are compared within the standard tilted flat ΛCDM model. While both P18 data and non-CMB data separately favor a closed geometry, with spatial curvature density parameter Ω k < 0, when P18+non-CMB data are jointly analyzed the evidence in favor of non-flat hypersurfaces subsides. Differences between P18 data and non-CMB data cosmological constraints subside when A L is allowed to vary. From the most restrictive P18+lensing+non-CMB data combination we get almost model-independent constraints on the cosmological parameters and find that the A L > 1 option is preferred over the Ω k < 0 one, with the A L parameter, for all models, being larger than unity by ~ 2.5σ. According to the deviance information criterion, in the P18+lensing+non-CMB analysis, the varying A L option is on the verge of being strongly favored over the A L = 1 one, which could indicate a problem for the standard tilted flat ΛCDM model. These data are consistent with flat spatial hypersurfaces but more and better data could improve the constraints on Ω k and might alter this conclusion. Error bars on some cosmological parameters are significantly reduced when non-CMB data are used jointly with P18+lensing data. For example, in the tilted flat ΛCDM model for P18+lensing+non-CMB data the Hubble constant H 0 = 68.09 ± 0.38 km s -1 Mpc -1 , which is consistent with that from a median statistics analysis of a large compilation of H 0 measurements as well as with a number of local measurements of the cosmological expansion rate. This H 0 error bar is 31% smaller than that from P18+lensing data alone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dark Energy Survey year 1 results: Constraints on extended cosmological models from galaxy clustering and weak lensing

We present constraints on extensions of the minimal cosmological models dominated by dark matter and dark energy, Lambda CDM and wCDM, by using a combined analysis of galaxy clustering and weak gravitational lensing from the first-year data of the Dark Energy Survey (DES Y1) in combination with external data. We consider four extensions of the minimal dark energy-dominated scenarios: (1) nonzero curvature Omega(k), (2) number of relativistic species N-eff different from the standard value of 3.046, (3) time-varying equation-of-state of dark energy described by the parameters w(0) and w(a) (alternatively quoted by the values at the pivot redshift, w(p), and w(a)), and (4) modified gravity described by the parameters is mu(0) and Sigma(0) that modify the metric potentials. We also consider external information from Planck cosmic microwave background measurements; baryon acoustic oscillation measurements from SDSS, 6dF, and BOSS; redshift-space distortion measurements from BOSS; and type Ia supernova information from the Pantheon compilation of datasets. Constraints on curvature and the number of relativistic species are dominated by the external data; when these are combined with DES Y1, we find Omega(k) = 0.0020(-0.0032)(+0.0037) at the 68% confidence level, and the upper limit N-eff < 3.28(3.55) at 68% (95%) confidence, assuming a hard prior N-eff > 3.0. For the time-varying equation-of-state, we find the pivot value (w(p), w(a)) = (-0.91(-0.23)(+0.19), -0.57(-1.11)(+0.93)) at pivot redshift z(p )= 0.27 from DES alone, and (w(p), w(a)) = (-1.01(-0.04)(+0.04), -0.28(-0.48)(+0.37)) at z(p) = 0.20 from DES Y1 combined with external data; in either case we find no evidence for the temporal variation of the equation of state. For modified gravity, we find the present-day value of the relevant parameters to be Sigma(0) = 0.43(-)(0.29)(+0.28) from DES Y1 alone, and (Sigma(0), mu(0)) = (0.06(-0.07)(+0.08), -0.11(-0.46)(+0.42)) from DES Y1 combined with external data. These modified-gravity constraints are consistent with predictions from general relativity.

Abbott, T. M. C.↗
DOE OSTI2019

Direct Randomized Benchmarking for Multiqubit Devices

Benchmarking methods that can be adapted to multiqubit systems are essential for assessing the overall or “holistic” performance of nascent quantum processors. The current industry standard is Clifford randomized benchmarking (RB), which measures a single error rate that quantifies overall performance. But, scaling Clifford RB to many qubits is surprisingly hard. It has only been performed on one, two, and three qubits as of this writing. This reflects a fundamental inefficiency in Clifford RB: the n-qubit Clifford gates at its core have to be compiled into large circuits over the one- and two-qubit gates native to a device. As n grows, the quality of these Clifford gates quickly degrades, making Clifford RB impractical at relatively low n. In this Letter, we propose a direct RB protocol that mostly avoids compiling. Instead, it uses random circuits over the native gates in a device, which are seeded by an initial layer of Clifford-like randomization. We demonstrate this protocol experimentally on two to five qubits using the publicly available ibmqx5. We believe this to be the greatest number of qubits holistically benchmarked, and this was achieved on a freely available device without any special tuning up. Our protocol retains the simplicity and convenient properties of Clifford RB: it estimates an error rate from an exponential decay. But, it can be extended to processors with more qubits—we present simulations on 10+ qubits—and it reports a more directly informative and flexible error rate than the one reported by Clifford RB. Here, we show how to use this flexibility to measure separate error rates for distinct sets of gates, and we use this method to estimate the average error rate of a set of cnot gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Accelerating semantic graph databases on commodity clusters

We are developing a full software system for accelerating semantic graph databases on commodity cluster that scales to hundreds of nodes while maintaining constant query throughput. Our framework comprises a SPARQL to C++ compiler, a library of parallel graph methods and a custom multithreaded runtime layer, which provides a Partitioned Global Address Space (PGAS) programming model with fork/join parallelism and automatic load balancing over a commodity clusters. We present preliminary results for the compiler and for the runtime.

commodity clusters↗
DOE OSTI2024

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

Tensor algebra operations represent an important class of algorithms used across many applications, including machine learning, scientific computing, and data analytics. As a result, the efficient generation of custom accelerators for tensor operations has received increased attention. Previous efforts have produced automated tools enabling users to prototype and explore optimized accelerators. However, little effort has been focused on the host-accelerator interaction in these tools. Efficient use of hardware accelerators requires knowledge about the accelerator's capabilities (operations, data formats, and opcode support), the host CPU microarchitecture (e.g., memory hierarchy), the host-accelerator interface, and the application's features (which code regions should be mapped onto an accelerator). Manually rewriting the original applications to facilitate improved custom accelerator mapping is an error-prone and time-consuming endeavor. To cope with this, we propose AXI4MLIR, a new framework to automatically generate and optimize the communication between the host CPU and arbitrary accelerators that implement linear algebra algorithms. AXI4MLIR extends the MLIR compiler framework to automatically generate efficient host-accelerator driver code for accelerators with AXI-based interfaces. Our compiler extensions enable automatic driver code generation while carefully considering the host's memory hierarchy and target accelerator features. To demonstrate the flexibility and utility of AXI4MLIR, we test it with diverse use cases that include different types of accelerators, tiling scenarios, and dataflow schemes. We compare our experimental results to manual implementations of host-accelerator driver code and find that our approach can reduce CPU cache references by 56% and deliver up to a 1.65x speedup.

Bohm Agostini, Nicolas↗
DOE OSTI2021

Invited: Bambu: an Open-Source Research Framework for the High-Level Synthesis of Complex Applications

This paper presents the open-source High-Level Synthesis research framework Bambu. The framework provides an open-source starting point to experiment with new ideas across High-Level Synthesis, high-level verification and debugging, FPGA/ASIC design, design flow space exploration, and parallel hardware accelerator design. The tool accepts as input standard C/C++ specifications and compiler intermediate representations (IRs) coming from the well-known Clang/LLVM and GCC com- pilers. The broad spectrum and flexibility of input formats allow the electronic design automation (EDA) research community to explore and integrate new transformations and optimizations. The easily extendable modular framework already includes many op- timizations and HLS benchmarks. The integration with synthesis and verification backends (commercial and open-source) allows researchers to quickly test any new finding and easily obtain performance and resource usage metrics for a given application. Different FPGA devices are supported from several different vendors: AMD/XILINX, Intel/Altera, Lattice Semiconductor, and NanoXplore. Finally, integration with the OpenRoad open-source end-to-end silicon compiler perfectly fits with the recent push towards open-source EDA.

Ferrandi, Fabrizio↗
DOE OSTI2017

PRESAGE: Protecting Structured Address Generation against Soft Errors

Modern computer scaling trends in pursuit of larger component counts and power efficiency have, unfortunately, lead to less reliable hardware and consequently soft errors escaping into application data ("silent data corruptions"). Techniques to enhance system resilience hinge on the availability of efficient error detectors that have high detection rates, low false positive rates, and lower computational overhead. Unfortunately, efficient detectors to detect faults during address generation (to index large arrays) have not been widely researched. We present a novel lightweight compiler-driven technique called PRESAGE for detecting bit-flips affecting structured address computations. A key insight underlying PRESAGE is that any address computation scheme that flows an already incurred error is better than a scheme that corrupts one particular array access but otherwise (falsely) appears to compute perfectly. Enabling the flow of errors allows one to situate detectors at loop exit points, and helps turn silent corruptions into easily detectable error situations. Our experiments using PolyBench benchmark suite indicate that PRESAGE-based error detectors have a high error-detection rate while incurring low overheads.

Sharma, Vishal C.↗
DOE OSTI2021

Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators

The growing numbers of application areas for artificial intelligence (AI) methods have led to an explosion of domain-specific accelerators that could support every new machine learning (ML) algorithm advancement, clearly highlighting the need for a capability to quickly and automatically transition from algorithm definition to hardware implementation and explore design space along a variety of SWaP (size, weight and Power). The software defined architectures (SODA) synthesizer implements a compiler-based modular infrastructure for the end-to-end generation of machine learning accelerators from high-level frameworks to hardware description language. At the same time, neuromorphic computing, by mimicking how the brain operates, promises to perform artificial intelligence tasks at efficiencies orders of magnitude higher than the current conventional tensor-processing based accelerators, as demonstrated by a variety of specialized designs leveraging Spiking Neural Networks (SNNs). Nevertheless, the mapping of an artificial neural network (ANN) to solutions supporting SNNs is still a non-trivial and very device-specific task, and completely lack the possibility to design hybrid systems that integrate conventional and spiking neural models. In this paper we discuss the support for such an integrated generation leveraging the SODA Synthesizer framework and its modular structure. In particular, we present a new MLIR dialect (part of the SODA frontend) that allows expressing spiking neural network features (e.g., available resources, spiking sequences, analog signal reading, etc.) and illustrate how it enables mapping to Spiking Neurons and deployment to the related specialized hardware (which, in the digital domain, could be generated through the other existing layers of the SODA Synthesizer). We then discuss the opportunities for even deeper integration afforded by the hardware compilation infrastructure, providing a path towards the generation of complex heterogeneous artificial intelligence systems.

Curzel, Serena↗
DOE OSTI2014

HERCULES: Strong Patterns towards More Intelligent Predictive Modeling, In: 2014 43rd International Conference on Parallel Processing

Recent work has shown that program analysis techniques to select meaningful code features of programs are important in the task of deciding the best compiler optimizations. Although, there are many successful state-of-the-art program analysis techniques, they often do not provide a simple method to extract the most expressive information about loops, especially when a target program is computationally intensive with complex loops and data dependencies. In this paper, we introduce a static technique to characterize a program using a pattern-driven system named HERCULES. This characterization technique not only helps a user to understand programs by searching pattern-of-interests, but also can be used for a predictive model that effectively selects the proper compiler optimizations. We formulated 35 loop patterns, then evaluated our characterization technique by comparing the predictive models constructed using HERCULES to three other state-of-the-art characterization methods. We show that our models outperform three state-of-the-art program characterization techniques on two multicore systems in selecting the best optimization combination from a given loop transformation space. We achieved up to 67% of the best possible speedup achievable with the optimization search space we evaluated.

Computer Science↗
DOE OSTI2024

Computing with a Chemical Reservoir

Contemporary computation is expensive, with large language models and artificial intelligence becoming more common in daily life. However, high-performance computing is reaching the limits in speed and energy expenditure, and domain science requires ever-increasing computational capacity, with simulations and data analysis pipelines ever-growing in complexity. As we progress towards post-exascale computation, with the associated high energy costs, new methods of energy-conscious computation are required. Novel analog and hybrid digital-analog systems can overcome these challenges, and chemical reactions offer a promising avenue. Computers based on chemistry can provide compact desktop devices with immense computational power. These devices are readily scalable by considering greater reaction systems or vessels, meeting the high-performance requirements for scientific workflows. In this article, we present ChemComp, a compilation pipeline for the conversion of ordinary differential equations into implementable chemical reactions. We then demonstrate the solving capabilities of ChemComp by emulating a potential chemical reservoir device. We leverage the multi-layer intermediate representation (MLIR) compiler framework to implement an expressive chemical reaction abstraction and propose a path for chemical reaction networks (CRNs) to represent mathematical problems effectively. Combined, we demonstrate a potential workflow that can harness chemistry’s computing power to create energy-efficient, high-performance computation systems for contemporary computing needs.

artificial intelligence↗