Recent lbnl_cs_cr items

A Novel Multi-level Integrated Roofline Model Approach for Performance Characterization

Wed, 10 Sep 2025 00:00:00 +0000

With energy-efficient architectures, including accelerators and many-core processors, gaining traction, application developers face the challenge of optimizing their applications for multiple hardware features including many-core parallelism, wide processing vector-units and on-chip high-bandwidth memory. In this paper, we discuss the development and utilization of a new application performance tool based on an extension of the classical roofline-model for simultaneously profiling multiple levels in the cache-memory hierarchy. This tool presents a powerful visual aid for the developer and can be used to frame the many-dimensional optimization problem in a tractable way. We show case studies of real scientific applications that have gained insights from the Integrated Roofline Model.

Experiences of Applying One-Sided Communication to Nearest-Neighbor Communication

Wed, 10 Sep 2025 00:00:00 +0000

Experiences of Applying One-Sided Communication to Nearest-Neighbor Communication

Performance analysis and optimization of the RAMPAGE metal alloy potential generation software

Wed, 10 Sep 2025 00:00:00 +0000

The Rapid Alloy Method for Producing Accurate, General Empirical potential generation toolkit (RAMPAGE) is a program for fitting multicomponent interatomic potential functions for metal alloys. In this paper, we describe a collaborative effort between domain scientists and performance engineers to improve the parallelism, scalability, and maintainability of the code. We modified RAMPAGE to use the Message Passing Interface (MPI) for communication and synchronization, to use more than one MPI process when evaluating candidate potential functions, and to have its MPI processes execute functionality that was previously executed by external non-MPI processes. We ported RAMPAGE to run on the Eos and Titan Cray systems of the United States Department of Energy (DOE)'s Oak Ridge Leadership Computing Facility (OLCF), and the Cori and Edison systems at the DOE's National Energy Research Scientific Computing Center (NERSC). Our modifications resulted in a 7 speedup on 8 Eos system nodes,...

Measurement of Bs0 and Ds- Meson Lifetimes

Wed, 7 Feb 2024 00:00:00 +0000

We report on a measurement of the flavor-specific B_{s}^{0} lifetime and of the D_{s}^{-} lifetime using proton-proton collisions at center-of-mass energies of 7 and 8 TeV, collected by the LHCb experiment and corresponding to 3.0 fb^{-1} of integrated luminosity. Approximately 407 000 B_{s}^{0}→D_{s}^{(*)-}μ^{+}ν_{μ} decays are partially reconstructed in the K^{+}K^{-}π^{-}μ^{+} final state. The B_{s}^{0} and D_{s}^{-} natural widths are determined using, as a reference, kinematically similar B^{0}→D^{(*)-}μ^{+}ν_{μ} decays reconstructed in the same final state. The resulting differences between widths of B_{s}^{0} and B^{0} mesons and of D_{s}^{-} and D^{-} mesons are Δ_{Γ}(B)=-0.0115±0.0053(stat)±0.0041(syst) ps^{-1} and Δ_{Γ}(D)=1.0131±0.0117(stat)±0.0065(syst) ps^{-1}, respectively. Combined with the known B^{0} and D^{-} lifetimes, these yield the flavor-specific B_{s}^{0} lifetime, τ_{B_{s}^{0}}^{fs}=1.547±0.013(stat)±0.010(syst)±0.004(τ_{B}) ps and the D_{s}^{-}...

Measurement of the properties of the Ξb∗ 0 baryon

Wed, 31 Jan 2024 00:00:00 +0000

We perform a search for near-threshold Ξb0 resonances decaying to Ξb−π+ in a sample of proton-proton collision data corresponding to an integrated luminosity of 3 fb−1 collected by the LHCb experiment. We observe one resonant state, with the following properties: (Formula presented.). This confirms the previous observation by the CMS collaboration. The state is consistent with the JP = 3/2+ Ξb∗0 resonance expected in the quark model. This is the most precise determination of the mass and the first measurement of the natural width of this state. We have also measured the ratio (Formula presented.).

Measurements of prompt charm production cross-sections in pp collisions at s=5 TeV

Wed, 10 Jan 2024 00:00:00 +0000

Production cross-sections of prompt charm mesons are measured using data from pp collisions at the LHC at a centre-of-mass energy of 5 TeV. The data sample corresponds to an integrated luminosity of 8.60 ± 0.33 pb−1 collected by the LHCb experiment. The production cross-sections of D0, D+, Ds+, and D∗+ mesons are measured in bins of charm meson transverse momentum, pT, and rapidity, y. They cover the rapidity range 2.0 < y < 4.5 and transverse momentum ranges 0 < pT< 10 GeV/c for D0 and D+ and 1 < pT< 10 GeV/c for Ds+ and D∗+ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of 1 < pT< 8 GeV/c are determined to be σpp→D0X=1004±3±54μb,σpp→D+X=402±2±30μb,σpp→Ds+X=170±4±16μb,σpp→D∗+X=421±5±36μb,$$ \begin{array}{l}\sigma \left( pp\to {D}^0X\right)=1004\pm 3\pm 54\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}^{+}X\right)=402\pm 2\pm 30\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}_s^{+}X\right)=170\pm 4\pm...

Surrogate optimization of deep neural networks for groundwater predictions

Tue, 6 Jun 2023 00:00:00 +0000

Sustainable management of groundwater resources under changing climatic conditions require an application of reliable and accurate predictions of groundwater levels. Mechanistic multi-scale, multi-physics simulation models are often too hard to use for this purpose, especially for groundwater managers who do not have access to the complex compute resources and data. Therefore, we analyzed the applicability and performance of four modern deep learning computational models for predictions of groundwater levels. We compare three methods for optimizing the models’ hyperparameters, including two surrogate model-based algorithms and a random sampling method. The models were tested using predictions of the groundwater level in Butte County, California, USA, taking into account the temporal variability of streamflow, precipitation, and ambient temperature. Our numerical study shows that the optimization of the hyperparameters can lead to reasonably accurate performance of all models (root...

Impact of Input Feature Selection on Groundwater Level Prediction From a Multi-Layer Perceptron Neural Network

Tue, 6 Jun 2023 00:00:00 +0000

With the growing use of machine learning (ML) techniques in hydrological applications, there is a need to analyze the robustness, performance, and reliability of predictions made with these ML models. In this paper we analyze the accuracy and variability of groundwater level predictions obtained from a Multilayer Perceptron (MLP) model with optimized hyperparameters for different amounts and types of available training data. The MLP model is trained on point observations of features like groundwater levels, temperature, precipitation, and river flow in various combinations, for different periods and temporal resolutions. We analyze the sensitivity of the MLP predictions at three different test locations in California, United States and derive recommendations for training features to obtain accurate predictions. We show that the use of all available features and data for training the MLP does not necessarily ensure the best predictive performance at all locations. More specifically,...

Mixed TDP-43 proteinopathy and tauopathy in frontotemporal lobar degeneration: nine case series

Tue, 23 May 2023 00:00:00 +0000

ObjectivesTo determine the clinical, anatomical, genetic and pathological features of dual frontotemporal lobar degeneration (FTLD) pathology: FTLD-tau and FTLD-TDP-43 in a large clinicopathological cohort.MethodsWe selected subjects with mixed FTLD-TDP and FTLD-tau from 247 FTLD cases from the University of California, San Francisco, Neurodegenerative Disease Brain Bank collected between 2000 and 2016 and compared their clinical, anatomical, genetic, imaging and pathological signatures with those of subjects with pure FTLD.ResultsWe found nine cases (3.6%) with prominent FTLD-TDP and FTLD-tau. Six cases were sporadic, whereas one case had a C9ORF72 expansion, another had a TARDBP A90V variant, and the other had an MAPT p.A152T variant. The subtypes of FTLD-TDP and FTLD-tau varied. Mixed FTLD cases were older and tended to show a higher burden of Alzheimer disease pathology (3/9, 33%). The neuroimaging signature of mixed cases, in general, included more widespread atrophy than...

Probing the correlation of neuronal loss, neurofibrillary tangles, and cell death markers across the Alzheimer's disease Braak stages: a quantitative study in humans

Sun, 14 May 2023 00:00:00 +0000

Clarifying the mechanisms connecting neurofibrillary tangle (NFT) neurotoxicity to neuronal dysfunction in humans is likely to be pivotal for developing effective treatments for Alzheimer's disease (AD). To model the temporal progression of AD in humans, we used a collection of brains with controls and individuals from each Braak stage to quantitatively investigate the correlation between intraneuronal caspase activation or macroautophagy markers, NFT burden, and neuronal loss, in the dorsal raphe nucleus and locus coeruleus, the earliest vulnerable areas to NFT accumulation. We fit linear regressions with each count as outcomes, with Braak score and age as the predictors. In progressive Braak stages, intraneuronal active caspase-6 positivity increases both alone and overlapping with NFTs. Likewise, the proportion of NFT-bearing neurons showing autophagosomes increases. Overall, caspases may be involved in upstream cascades in AD and are associated with higher NFTs. Macroautophagy...

On the numerical accuracy in finite‐volume methods to accurately capture turbulence in compressible flows

Thu, 8 Dec 2022 00:00:00 +0000

Abstract The goal of the present article is to understand the impact of numerical schemes for the reconstruction of data at cell faces in finite‐volume methods, and to assess their interaction with the quadrature rule used to compute the average over the cell volume. Here, third‐, fifth‐ and seventh‐order WENO‐Z schemes are investigated. On a problem with a smooth solution, the theoretical order of convergence rate for each method is retrieved, and changing the order of the reconstruction at cell faces does not impact the results, whereas for a shock‐driven problem all the methods collapse to first‐order. Study of the decay of compressible homogeneous isotropic turbulence reveals that using a high‐order quadrature rule to compute the average over a finite‐volume cell does not improve the spectral accuracy and that all methods present a second‐order convergence rate. However the choice of the numerical method to reconstruct data at cell faces is found to be critical to correctly...

The divergence of nearby trajectories in soft-sphere DEM

Tue, 6 Dec 2022 00:00:00 +0000

The n-body instability is investigated with the soft-sphere discrete element method. The divergence of nearby trajectories is quantified by the dynamical memory time. Using the inverse proportionality between the dynamical memory time and the largest Lyapunov exponent, the soft-sphere discrete element method results are compared to previous hard-sphere molecular dynamics data for the first time. Good agreement is observed at low concentrations and the degree of instability is shown to increase asymptotically with increasing spring stiffness. At particle concentrations above 30%, the soft-sphere Lyapunov exponents increase faster than the corresponding hard-sphere data. This paper concludes with a demonstration of how this case study may be used in conjunction with regression testing and code verification activities.

The Discovery of a Highly Accreting, Radio-loud Quasar at z = 6.82

Sat, 9 Apr 2022 00:00:00 +0000

Radio sources at the highest redshifts can provide unique information on the first massive galaxies and black holes, the densest primordial environments, and the epoch of reionization. The number of astronomical objects identified at z > 6 has increased dramatically over the last few years, but previously only three radio-loud (R 2500 = f ν,5 GHz/f ν,2500 Å > 10) sources had been reported at z > 6, with the most distant being a quasar at z = 6.18. Here we present the discovery and characterization of PSO J172.3556+18.7734, a radio-loud quasar at z = 6.823. This source has an Mg ii-based black hole mass of ∼3 × 108 M o˙ and is one of the fastest accreting quasars, consistent with super-Eddington accretion. The ionized region around the quasar is among the largest measured at these redshifts, implying an active phase longer than the average lifetime of the z ⪆ 6 quasar population. From archival data, there is evidence that its 1.4 GHz emission has decreased by a factor...

Mitigating Depolarizing Noise on Quantum Computers with Noise-Estimation Circuits

Tue, 1 Feb 2022 00:00:00 +0000

A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise for large circuits involving many qubits and gates. We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit and then correcting the output of the target circuit using the estimated rate. The method is experimentally validated on a simulation of the Heisenberg model. We find that our approach in combination with readout-error correction, randomized compiling, and zero-noise extrapolation produces close to exact results even for circuits containing hundreds of CNOT gates. We also show analytically that zero-noise extrapolation is improved when it is applied to the output of our method.

MFIX-Exa: A path toward exascale CFD-DEM simulations

Wed, 19 Jan 2022 00:00:00 +0000

MFIX-Exa is a computational fluid dynamics–discrete element model (CFD-DEM) code designed to run efficiently on current and next-generation supercomputing architectures. MFIX-Exa combines the CFD-DEM expertise embodied in the MFIX code—which was developed at NETL and is used widely in academia and industry—with the modern software framework, AMReX, developed at LBNL. The fundamental physics models follow those of the original MFIX, but the combination of new algorithmic approaches and a new software infrastructure will enable MFIX-Exa to leverage future exascale machines to optimize the modeling and design of multiphase chemical reactors.

Pōniuā‘ena: A Luminous z = 7.5 Quasar Hosting a 1.5 Billion Solar Mass Black Hole

Tue, 14 Dec 2021 00:00:00 +0000

We report the discovery of a luminous quasar, J1007+2115 at z = 7.515 ("Poniua'ena"), from our wide-field reionization-era quasar survey. J1007+2115 is the second quasar now known at z > 7.5, deep into the reionization epoch. The quasar is powered by a (1.5 ± 0.2) × 109 M o supermassive black hole (SMBH), based on its broad Mg ii emission-line profile from Gemini and Keck near-IR spectroscopy. The SMBH in J1007+2115 is twice as massive as that in quasar J1342+0928 at z = 7.54, the current quasar redshift record holder. The existence of such a massive SMBH just 700 million years after the Big Bang significantly challenges models of the earliest SMBH growth. Model assumptions of Eddington-limited accretion and a radiative efficiency of 0.1 require a seed black hole of 104 M o at z = 30. This requirement suggests either a massive black hole seed as a result of direct collapse or earlier periods of rapid black hole growth with hyper-Eddington accretion and/or a low radiative efficiency....

A Luminous Quasar at Redshift 7.642

Mon, 13 Dec 2021 00:00:00 +0000

Distant quasars are unique tracers to study the formation of the earliest supermassive black holes (SMBHs) and the history of cosmic reionization. Despite extensive efforts, only two quasars have been found at z ≥7.5, due to a combination of their low spatial density and the high contamination rate in quasar selection. We report the discovery of a luminous quasar at z = 7.642, J0313-1806, the most distant quasar yet known. This quasar has a bolometric luminosity of 3.6 × 1013Le. Deep spectroscopic observations reveal a SMBH with a mass of (1.6 ± 0.4) × 109M⊙ in this quasar. The existence of such a massive SMBH just ∼670 million years after the big bang challenges significantly theoretical models of SMBH growth. In addition, the quasar spectrum exhibits strong broad absorption line (BAL) features in C IV and Si IV, with a maximum velocity close to 20% of the speed of light. The relativistic BAL features, combined with a strongly blueshifted C IV emission line, indicate that there...

A Significantly Neutral Intergalactic Medium Around the Luminous z = 7 Quasar J0252–0503

Mon, 13 Dec 2021 00:00:00 +0000

Luminous z ≥ 7 quasars provide direct probes of the evolution of supermassive black holes (SMBHs) and the intergalactic medium (IGM) during the epoch of reionization (EoR). The Lyα damping wing absorption imprinted by neutral hydrogen in the IGM can be detected in a single EoR quasar spectrum, allowing the measurement of the IGM neutral fraction toward that line of sight. However, damping wing features have only been detected in two z > 7 quasars in previous studies. In this paper, we present new high-quality optical and near-infrared spectroscopy of the z = 7.00 quasar DES J025216.64-050331.8 obtained with Keck/Near-Infrared Echellette Spectrometer and Gemini/GMOS. By using the Mg ii single-epoch virial method, we find that it hosts a SMBH accreting at an Eddington ratio of λ Edd = 0.7 0.1, consistent with the values seen in other luminous z ∼ 7 quasars. Furthermore, the Lyα region of the spectrum exhibits a strong damping wing absorption feature. The lack of associated metal...

Parallel-In-Time Magnus Integrators

Wed, 25 Aug 2021 00:00:00 +0000

Magnus integrators are a subset of geometric integration methods for the numerical solution of ordinary differential equations that conserve certain invariants in the numerical solution. This paper explores temporal parallelism of Magnus integrators, particularly in the context of nonlinear problems. The approach combines the concurrent computation of matrix commutators and exponentials within a time step with a pipelined iteration applied to multiple time steps in parallel. The accuracy and efficiency of time parallel Magnus methods up to order six are highlighted through numerical examples and demonstrate that significant parallel speedup is possible compared to serial methods.

Ring artifact reduction via multiscale nonlocal collaborative filtering of spatially correlated noise

Mon, 26 Jul 2021 00:00:00 +0000

X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.

Mitigating depolarizing noise on quantum computers with noise-estimation circuits

Tue, 30 Mar 2021 00:00:00 +0000

A significant problem for current quantum computers is noise. While there are many distinct noise channels, the depolarizing noise model often appropriately describes average noise for large circuits involving many qubits and gates. We present a method to mitigate the depolarizing noise by first estimating its rate with a noise-estimation circuit and then correcting the output of the target circuit using the estimated rate. The method is experimentally validated on the simulation of the Heisenberg model. We find that our approach in combination with readout-error correction, randomized compiling, and zero-noise extrapolation produces results close to exact results even for circuits containing hundreds of CNOT gates.

Real time evolution for ultracompact Hamiltonian eigenstates on quantum hardware

Tue, 30 Mar 2021 00:00:00 +0000

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time evolved expansion states, and connects the method to the classical filter diagonalization algorithm. Further, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise which substantially improves previous considerations. The unitary formulation...

SHARP: a distributed GPU-based ptychographic solver

Tue, 2 Feb 2021 00:00:00 +0000

Ever brighter light sources, fast parallel detectors and advances in phase retrieval methods have made ptychography a practical and popular imaging technique. Compared to previous techniques, ptychography provides superior robustness and resolution at the expense of more advanced and time-consuming data analysis. By taking advantage of massively parallel architectures, high-throughput processing can expedite this analysis and provide microscopists with immediate feedback. These advances allow real-time imaging at wavelength-limited resolution, coupled with a large field of view. This article describes a set of algorithmic and computational methodologies used at the Advanced Light Source and US Department of Energy light sources. These are packaged as a CUDA-based software environment named SHARP (http://camera.lbl.gov/sharp), aimed at providing state-of-the-art high-throughput ptychography reconstructions for the coming era of diffraction-limited light sources.

Simulating Quantum Materials with Digital Quantum Computers

Tue, 2 Feb 2021 00:00:00 +0000

Quantum materials exhibit a wide array of exotic phenomena and practically useful properties. A better understanding of these materials can provide deeper insights into fundamental physics in the quantum realm as well as advance technology for entertainment, healthcare, and sustainability. The emergence of digital quantum computers (DQCs), which can efficiently perform quantum simulations that are otherwise intractable on classical computers, provides a promising path forward for testing and analyzing the remarkable, and often counter-intuitive, behavior of quantum materials. Equipped with these new tools, scientists from diverse domains are racing towards achieving physical quantum advantage (i.e., using a quantum computer to learn new physics with a computation that cannot feasibly be run on any classical computer). The aim of this review, therefore, is to provide a summary of progress made towards this goal that is accessible to scientists across the physical sciences. We will first...

A statistical model to predict ignition probability

Tue, 19 Jan 2021 00:00:00 +0000

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. This work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the...

An ultrahigh-resolution soft x-ray microscope for quantitative analysis of chemically heterogeneous nanomaterials

Mon, 11 Jan 2021 00:00:00 +0000

The analysis of chemical states and morphology in nanomaterials is central to many areas of science. We address this need with an ultrahigh-resolution scanning transmission soft x-ray microscope. Our instrument provides multiple analysis tools in a compact assembly and can achieve few-nanometer spatial resolution and high chemical sensitivity via x-ray ptychography and conventional scanning microscopy. A novel scanning mechanism, coupled to advanced x-ray detectors, a high-brightness x-ray source, and high-performance computing for analysis provide a revolutionary step forward in terms of imaging speed and resolution. We present x-ray microscopy with 8-nm full-period spatial resolution and use this capability in conjunction with operando sample environments and cryogenic imaging, which are now routinely available. Our multimodal approach will find wide use across many fields of science and facilitate correlative analysis of materials with other types of probes.

One-dimensional phase retrieval: regularization, box relaxation and uniqueness

Thu, 12 Nov 2020 00:00:00 +0000

Recovering a signal from its Fourier magnitude is referred to as phase retrieval, which occurs in different fields of engineering and applied physics. This paper gives a new characterization of the phase retrieval problem. Particularly useful is the analysis revealing that the common gradient-based regularization does not restrict the set of solutions to a smaller set. Specifically focusing on binary signals, we show that a box relaxation is equivalent to the binary constraint for Fourier-types of phase retrieval. We further prove that binary signals can be recovered uniquely up to trivial ambiguities under certain conditions. Finally, we use the characterization theorem to develop an efficient denoising algorithm.

Analyzer-free linear dichroic ptychography1

Wed, 11 Nov 2020 00:00:00 +0000

Linear dichroism is an important tool to characterize the transmission matrix and determine the crystal or orbital orientation in a material. In order to achieve high-resolution mapping of transmission properties, the linear-dichroism scattering model in ptychographic imaging is introduced, and an efficient two-stage reconstruction algorithm is developed. Using the proposed algorithm on a uniaxial material, the dichroic transmission matrix can be recovered without an analyzer by using ptychography measurements with as few as three different polarization angles, with the help of an empty region to remove phase ambiguities.

Error detection on quantum computers improving the accuracy of chemical calculations

Tue, 15 Sep 2020 00:00:00 +0000

A major milestone of quantum error correction is to achieve the fault-tolerance threshold beyond which quantum computers can be made arbitrarily accurate. This requires extraordinary resources and engineering efforts. We show that, even without achieving full fault tolerance, quantum error detection is already useful on the current generation of quantum hardware. We demonstrate this experimentally by executing an end-to-end chemical calculation for the hydrogen molecule encoded in the [[4, 2, 2]] quantum error-detecting code. The encoded calculation with logical qubits significantly improves the accuracy of the molecular ground-state energy.

SUGAR: An improved empirical model of Type Ia supernovae based on spectral features

Wed, 19 Aug 2020 00:00:00 +0000

© P.-F. Léget et al. 2020. Context. Type Ia supernovae (SNe Ia) are widely used to measure the expansion of the Universe. Improving distance measurements of SNe Ia is one technique to better constrain the acceleration of expansion and determine its physical nature. Aims. This document develops a new SNe Ia spectral energy distribution (SED) model, called the SUpernova Generator And Reconstructor (SUGAR), which improves the spectral description of SNe Ia, and consequently could improve the distance measurements. Methods. This model was constructed from SNe Ia spectral properties and spectrophotometric data from the Nearby Supernova Factory collaboration. In a first step, a principal component analysis-like method was used on spectral features measured at maximum light, which allowed us to extract the intrinsic properties of SNe Ia. Next, the intrinsic properties were used to extract the average extinction curve. Third, an interpolation using Gaussian processes facilitated using...

Sparse Matrix-Based HPC Tomography

Mon, 17 Aug 2020 00:00:00 +0000

Abstract Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. The solution...

Iterative X-ray spectroscopic ptychography1

Mon, 17 Aug 2020 00:00:00 +0000

Spectroscopic ptychography is a powerful technique to determine the chemical composition of a sample with high spatial resolution. In spectro-ptychography, a sample is rastered through a focused X-ray beam with varying photon energy so that a series of phaseless diffraction data are recorded. Each chemical component in the material under investigation has a characteristic absorption and phase contrast as a function of photon energy. Using a dictionary formed by the set of contrast functions of each energy for each chemical component, it is possible to obtain the chemical composition of the material from high-resolution multi-spectral images. This paper presents SPA (spectroscopic ptychography with alternating direction method of multipliers), a novel algorithm to iteratively solve the spectroscopic blind ptychography problem. First, a nonlinear spectro-ptychography model based on Poisson maximum likelihood is designed, and then the proposed method is constructed on the basis of...

An Examination and Survey of Random Bit Flips and Scientific Computing

Sun, 26 Jul 2020 00:00:00 +0000

Data error, modification, and loss can occur in scientific computing due to numerous potential causes, including those natural, accidental, or malicious in nature. Such errors and modifications can silently impact scientific computing results if not detected and corrected or compensated for through other means. The goal of this document is to describe the ways in which integrity faults due to bit flips occur, their potential odds of occurring, and potential mitigation mechanisms in high-level, practical terms, and is broken into individual computer components and environments describing each of those elements. We conclude the report by summarizing key issues and several best practices for mitigation of the effects of bit flip-induced errors.

Reionization history constraints from neural network based predictions of high-redshift quasar continua

Tue, 7 Jul 2020 00:00:00 +0000

Observations of the early Universe suggest that reionization was complete by z ~ 6, however, the exact history of this process is still unknown. One method for measuring the evolution of the neutral fraction throughout this epoch is via observing the Lya damping wings of high-redshift quasars. In order to constrain the neutral fraction from quasar observations, one needs an accurate model of the quasar spectrum around Lya, after the spectrum has been processed by its host galaxy but before it is altered by absorption and damping in the intervening intergalactic medium (IGM). In this paper,we present a novelmachine learning approach, using artificial neural networks, to reconstruct quasar continua around Lyα. Our Quasar Spectra from Artificial Neural Network based predictive Regression Algorithm (QSANNDRA) improves the error in this reconstruction compared to the state-of-the-art principal component analysis (PCA) based model in the literature by 14.2 per cent on average, and provides...

Detecting and Characterizing Young Quasars. I. Systemic Redshifts and Proximity Zone Measurements

Tue, 7 Jul 2020 00:00:00 +0000

In a multiwavelength survey of 13 quasars at 5.8 ≲ z ≲ 6.5, which were preselected to be potentially young, we find five objects with extremely small proximity zone sizes that may imply UV-luminous quasar lifetimes of ≲100,000 yr. Proximity zones are regions of enhanced transmitted flux in the vicinity of quasars that are sensitive to the quasars' lifetimes because the intergalactic gas has a finite response time to their radiation. We combine submillimeter observations from the Atacama Large Millimetre Array and the NOrthern Extended Millimeter Array, as well as deep optical and near-infrared spectra from the medium-resolution spectrograph on the Very Large Telescope and on the Keck telescopes, in order to identify and characterize these new young quasars, which provide valuable clues about the accretion behavior of supermassive black holes in the early universe and pose challenges on current black hole formation models to explain the rapid formation of billion-solar-mass black...

PypeIt: The Python Spectroscopic Data Reduction Pipeline

Tue, 7 Jul 2020 00:00:00 +0000

PypeIt is a Python package for semi-automated reduction of astronomical, spectroscopic data. Its algorithms build on decades-long development of previous data reduction pipelines by the developers (Bernstein, Burles, & Prochaska, 2015; Bochanski et al., 2009). The reduction procedure -- including a complete list of the input parameters and available functionality -- is provided as online documentation hosted by Read the Docs, which is regularly updated. (https://pypeit.readthedocs.io/en/latest/). Release v1.0.3 serves the following spectrographs: Gemini/GNIRS, Gemini/GMOS, Gemini/FLAMINGOS 2, Lick/Kast, Magellan/MagE, Magellan/Fire, MDM/OSMOS, Keck/DEIMOS (600ZD, 830G, 1200G), Keck/LRIS, Keck/MOSFIRE (J and Y gratings tested), Keck/NIRES, Keck/NIRSPEC (low-dispersion), LBT/Luci-I, Luci-II, LBT/MODS (beta), NOT/ALFOSC (grism4), VLT/X-Shooter (VIS, NIR), VLT/FORS2 (300I, 300V), WHT/ISIS.

Studies of the resonance structure in D0→K∓π±π±π∓ decays

Wed, 27 May 2020 00:00:00 +0000

Amplitude models are constructed to describe the resonance structure of D0→K-π+π+π-$${D^{0}\rightarrow K^{-}\pi ^{+}\pi ^{+}\pi ^{-}}$$ and D0→K+π-π-π+$${D^{0} \rightarrow K^{+}\pi ^{-}\pi ^{-}\pi ^{+}}$$ decays using pp collision data collected at centre-of-mass energies of 7 and 8 TeV with the LHCb experiment, corresponding to an integrated luminosity of 3.0 fb-1$$fb^{-1}$$. The largest contributions to both decay amplitudes are found to come from axial resonances, with decay modes D0→a1(1260)+K-$$D^{0} \rightarrow a_1(1260)^{+} K^{-}$$ and D0→K1(1270/1400)+π-$$D^{0} \rightarrow K_1(1270/1400)^{+} \pi ^{-}$$ being prominent in D0→K-π+π+π-$${D^{0}\rightarrow K^{-}\pi ^{+}\pi ^{+}\pi ^{-}}$$ and D0→K+π-π-π+$$D^{0}\rightarrow K^{+}\pi ^{-}\pi ^{-}\pi ^{+}$$, respectively. Precise measurements of the lineshape parameters and couplings of the a1(1260)+$$a_1(1260)^{+}$$, K1(1270)-$$K_1(1270)^{-}$$ and K(1460)-$$K(1460)^{-}$$ resonances are made, and a quasi model-independent...

Time-resolved protein nanocrystallography using an X-ray free-electron laser

Sun, 17 May 2020 00:00:00 +0000

We demonstrate the use of an X-ray free electron laser synchronized with an optical pump laser to obtain X-ray diffraction snapshots from the photoactivated states of large membrane protein complexes in the form of nanocrystals flowing in a liquid jet. Light-induced changes of Photosystem I-Ferredoxin co-crystals were observed at time delays of 5 to 10 µs after excitation. The result correlates with the microsecond kinetics of electron transfer from Photosystem I to ferredoxin. The undocking process that follows the electron transfer leads to large rearrangements in the crystals that will terminally lead to the disintegration of the crystals. We describe the experimental setup and obtain the first time-resolved femtosecond serial X-ray crystallography results from an irreversible photo-chemical reaction at the Linac Coherent Light Source. This technique opens the door to time-resolved structural studies of reaction dynamics in biological systems.

Simulating single-coil MRI from the responses of multiple coils

Tue, 14 Apr 2020 00:00:00 +0000

The aim of the present paper is to provide a comparison between several finitevolume methods of different numerical accuracy: the second-order Godunov method with PPM interpolation and the high-order finite-volume WENO method. The results show that while on a smooth problem the high-order method performs better than the second-order one, when the solution contains a shock all the methods collapse to first-order accuracy. In the context of the decay of compressible homogeneous isotropic turbulence with shocklets, the actual overall order of accuracy of the methods reduces to second-order, despite the use of fifth-order reconstruction schemes at cell interfaces. Most important, results in terms of turbulent spectra are similar regardless of the numerical methods employed, except that the PPM method fails to provide an accurate representation in the high-frequency range of the spectra. It is found that this specific issue comes from the slope-limiting procedure and a novel hybrid...

An Automated Disruption-Tolerant Key Management Framework for Critical Systems

Fri, 3 Apr 2020 00:00:00 +0000

Key management is critical to secure operation. Distributed control systems, such as Supervisory Control and Data Acquisition (SCADA) systems, have unique operational requirements that make conventional key management solutions less effectiveand burdensome. This paper pres-ents a novel Kerberos-based framework for automated, disruption-tolerant key management for control system environments. Experimental tests and their results are presented to quantify the expected performance overhead of this approach. Additionally, Zeek sensor analytics are presented to aid in monitoring the health and security of the key management framework operation.

Chemistry on quantum computers with virtual quantum subspace expansion

Tue, 17 Mar 2020 00:00:00 +0000

Several novel methods for performing calculations relevant to quantum chemistry on quantum computers have been proposed but not yet explored experimentally. Virtual quantum subspace expansion [T. Takeshita et al., Phys. Rev. X 10, 011004 (2020)] is one such algorithm developed for modeling complex molecules using their full orbital space and without the need for additional quantum resources. We implement this method on the IBM Q platform and calculate the potential energy curves of the hydrogen and lithium dimers using only two qubits and simple classical post-processing. A comparable level of accuracy would require twenty qubits with previous approaches. We also develop an approach to minimize the impact of experimental noise on the stability of a generalized eigenvalue problem that is a crucial component of the algorithm. Our results demonstrate that virtual quantum subspace expansion works well in practice.

Orthogonality constrained gradient reconstruction for superconvergent linear functionals

Sun, 9 Feb 2020 00:00:00 +0000

The post-processing of the solution of variational problems discretized with Galerkin finite element methods is particularly useful for the computation of quantities of interest. Such quantities are generally expressed as linear functionals of the solution and the error of their approximation is bounded by the error of the solution itself. Several a posteriori recovery procedures have been developed over the years to improve the accuracy of post-processed results. Nonetheless such recovery methods usually deteriorate the convergence properties of linear functionals of the solution and, as a consequence, of the quantities of interest as well. The paper develops an enhanced gradient recovery scheme able to both preserve the good qualities of the recovered gradient and increase the accuracy and the convergence rates of linear functionals of the solution.

Interactive volumetric segmentation for textile micro‐tomography data using wavelets and nonlocal means

Tue, 4 Feb 2020 00:00:00 +0000

This work addresses segmentation of volumetric images of woven carbon fiber textiles from micro‐tomography data. We propose a semi‐supervised algorithm to classify carbon fibers that requires sparse input as opposed to completely labeled images. The main contributions are: (a) design of effective discriminative classifiers, for three‐dimensional textile samples, trained on wavelet features for segmentation; (b) coupling of previous step with nonlocal means as simple, efficient alternative to the Potts model; and (c) demonstration of reuse of classifier to diverse samples containing similar content. We evaluate our work by curating test sets of voxels in the absence of a complete ground truth mask. The algorithm obtains an average 0.95 F1 score on test sets and average F1 score of 0.93 on new samples. We conclude with discussion of failure cases and propose future directions toward analysis of spatiotemporal high‐resolution micro‐tomography images.

Iterative Joint Ptychography-Tomography with Total Variation Regularization

Thu, 9 Jan 2020 00:00:00 +0000

In order to determine the 3D structure of a thick sample, researchers have recently combined ptychography (for high resolution) and tomography (for 3D imaging) in a single experiment. 2-step methods are usually adopted for reconstruction, where the ptychography and tomography problems are often solved independently. In this paper, we provide a novel model and ADMM-based algorithm to jointly solve the ptychography-tomography problem iteratively, also employing total variation regularization. The proposed method permits large scan stepsizes for the ptychography experiment, requiring less measurements and being more robust to noise with respect to other strategies, while achieving higher reconstruction quality results.

Unfolding quantum computer readout noise

Wed, 30 Oct 2019 00:00:00 +0000

In the current era of noisy intermediate-scale quantum computers, noisy qubits can result in biased results for early quantum algorithm applications. This is a significant challenge for interpreting results from quantum computer simulations for quantum chemistry, nuclear physics, high energy physics (HEP), and other emerging scientific applications. An important class of qubit errors are readout errors. The most basic method to correct readout errors is matrix inversion, using a response matrix built from simple operations to probe the rate of transitions from known initial quantum states to readout outcomes. One challenge with inverting matrices with large off-diagonal components is that the results are sensitive to statistical fluctuations. This challenge is familiar to HEP, where prior-independent regularized matrix inversion techniques (“unfolding”) have been developed for years to correct for acceptance and detector effects, when performing differential cross section measurements....

Error detection on quantum computers improving the accuracy of chemical calculations

Wed, 30 Oct 2019 00:00:00 +0000

Quantum Associative Memory in Hep Track Pattern Recognition

Mon, 28 Oct 2019 00:00:00 +0000

We have entered the Noisy Intermediate-Scale Quantum Era. A plethora of quantum processor prototypes allow evaluation of potential of the Quantum Computing paradigm in applications to pressing computational problems of the future. Growing data input rates and detector resolution foreseen in High-Energy LHC (2030s) experiments expose the often high time and/or space complexity of classical algorithms. Quantum algorithms can potentially become the lower-complexity alternatives in such cases. In this work we discuss the potential of Quantum Associative Memory (QuAM) in the context of LHC data triggering. We examine the practical limits of storage capacity, as well as store and recall errorless efficiency, from the viewpoints of the state-of-the-art IBM quantum processors and LHC real-time charged track pattern recognition requirements. We present a software prototype implementation of the QuAM protocols and analyze the topological limitations for porting the simplest QuAM instances...

A spectral deferred correction strategy for low Mach number reacting flows subject to electric fields

Wed, 16 Oct 2019 00:00:00 +0000

We propose an algorithm for low Mach number reacting flows subjected to electric field that includes the chemical production and transport of charged species. This work is an extension of a multi-implicit spectral deferred correction (MISDC) algorithm designed to advance the conservation equations in time at scales associated with advective transport. The fast and nontrivial interactions of electrons with the electric field are treated implicitly using a Jacobian-Free Newton Krylov approach for which a preconditioning strategy is developed. Within the MISDC framework, this enables a close and stable coupling of diffusion, reactions and dielectric relaxation terms with advective transport and is shown to exhibit second-order convergence in space and time. The algorithm is then applied to a series of steady and unsteady problems to demonstrate its capability and stability. Although developed in a one-dimensional case, the algorithmic ingredients are carefully designed to be amenable...

Chemical composition mapping with nanometre resolution by soft X-ray microscopy

Tue, 15 Oct 2019 00:00:00 +0000

X-ray microscopy is powerful in that it can probe large volumes of material at high spatial resolution with exquisite chemical, electronic and bond orientation contrast. The development of diffraction-based methods such as ptychography has, in principle, removed the resolution limit imposed by the characteristics of the X-ray optics. Here, using soft X-ray ptychography, we demonstrate the highest-resolution X-ray microscopy ever achieved by imaging 5â €..nm structures. We quantify the performance of our microscope and apply the method to the study of delithiation in a nanoplate of LiFePO 4, a material of broad interest in electrochemical energy storage. We calculate chemical component distributions using the full complex refractive index and demonstrate enhanced contrast, which elucidates a strong correlation between structural defects and chemical phase propagation. The ability to visualize the coupling of the kinetics of a phase transformation with the mechanical consequences...

A parallel hierarchical blocked adaptive cross approximation algorithm

Tue, 17 Sep 2019 00:00:00 +0000

This article presents a low-rank decomposition algorithm based on subsampling of matrix entries. The proposed algorithm first computes rank-revealing decompositions of submatrices with a blocked adaptive cross approximation (BACA) algorithm, and then applies a hierarchical merge operation via truncated singular value decompositions (H-BACA). The proposed algorithm significantly improves the convergence of the baseline ACA algorithm and achieves reduced computational complexity compared to the traditional decompositions such as rank-revealing QR. Numerical results demonstrate the efficiency, accuracy, and parallel scalability of the proposed algorithm.

Shaping coherent x-rays with binary optics.

Mon, 16 Sep 2019 00:00:00 +0000

Diffractive lenses fabricated by lithographic methods are one of the most popular image forming optics in the x-ray regime. Most commonly, binary diffractive optics, such as Fresnel zone plates, are used due to their ability to focus at high resolution and to manipulate the x-ray wavefront. We report here a binary zone plate design strategy to form arbitrary illuminations for coherent multiplexing, structured illumination, and wavefront shaping experiments. Given a desired illumination, we adjust the duty cycle, harmonic order, and zone placement to vary both the amplitude and phase of the wavefront at the lens. This enables the binary lithographic pattern to generate arbitrary structured illumination optimized for a variety of applications such as holography, interferometry, ptychography, imaging, and others.

Measurement of the ratio of branching fractions of the decays Λb0 → ψ(2S)Λ and Λb0 → J/ψΛ

Mon, 16 Sep 2019 00:00:00 +0000

Using pp collisions corresponding to 3 fb−1 integrated luminosity, recorded by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV, the ratio of branching fractions ℬΛb0→ψ2SΛ/ℬΛb0→J/ψΛ=0.513±0.023stat±0.016syst±0.011ℬ$$ \mathrm{\mathcal{B}}\left({\Lambda}_b^0\to \psi (2S)\Lambda \right)/\mathrm{\mathcal{B}}\left({\Lambda}_b^0\to J/\psi \Lambda \right)=0.513\pm 0.023\left(\mathrm{stat}\right)\pm 0.016\left(\mathrm{syst}\right)\pm 0.011\left(\mathrm{\mathcal{B}}\right) $$ is determined. The first uncertainty is statistical, the second is systematic and the third is due to the external branching fractions used.

Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients

Mon, 16 Sep 2019 00:00:00 +0000

We present a robust and scalable preconditioner for the solution of large-scale linear systems that arise from the discretization of elliptic PDEs amenable to rank compression. The preconditioner is based on hierarchical low-rank approximations and the cyclic reduction method. The setup and application phases of the preconditioner achieve log-linear complexity in memory footprint and number of operations, and numerical experiments exhibit good weak and strong scalability at large processor counts in a distributed memory environment. Numerical experiments with linear systems that feature symmetry and nonsymmetry, definiteness and indefiniteness, constant and variable coefficients demonstrate the preconditioner applicability and robustness. Furthermore, it is possible to control the number of iterations via the accuracy threshold of the hierarchical matrix approximations and their arithmetic operations, and the tuning of the admissibility condition parameter. Together, these parameters...

Search for the rare decay Bs0→μ+μ-

Fri, 13 Sep 2019 00:00:00 +0000

A search for the rare decay D0→μ+μ- is performed using a data sample, corresponding to an integrated luminosity of 0.9fb-1, of pp collisions collected at a centre-of-mass energy of 7 TeV by the LHCb experiment. The observed number of events is consistent with the background expectations and corresponds to an upper limit of B(D0→μ+μ-)<6.2(7.6)×10-9 at 90% (95%) confidence level. This result represents an improvement of more than a factor twenty with respect to previous measurements. © 2013 CERN.

Blind Ptychographic Phase Retrieval via Convergent Alternating Direction Method of Multipliers

Fri, 13 Sep 2019 00:00:00 +0000

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A ptychographic reconstruction is normally formulated as a blind phase retrieval problem, where both the image (sample) and the probe (illumination) have to be recovered from phaseless measured data. In this article we address a nonlinear least squares model for the blind ptychography problem with constraints on the image and the probe by maximum likelihood estimation of the Poisson noise model. We formulate a variant model that incorporates the information of phaseless measurements of the probe to eliminate possible artifacts. Next, we propose a generalized alternating direction method of multipliers designed for the proposed nonconvex models with convergence guarantee under mild conditions, where their subproblems can be solved by fast elementwise operations....

Advanced denoising for X-ray ptychography.

Fri, 13 Sep 2019 00:00:00 +0000

The success of ptychographic imaging experiments strongly depends on achieving high signal-to-noise ratio. This is particularly important in nanoscale imaging experiments when diffraction signals are very weak and the experiments are accompanied by significant parasitic scattering (background), outliers or correlated noise sources. It is also critical when rare events, such as cosmic rays, or bad frames caused by electronic glitches or shutter timing malfunction take place. In this paper, we propose a novel iterative algorithm with rigorous analysis that exploits the direct forward model for parasitic noise and sample smoothness to achieve a thorough characterization and removal of structured and random noise. We present a formal description of the proposed algorithm and prove its convergence under mild conditions. Numerical experiments from simulations and real data (both soft and hard X-ray beamlines) demonstrate that the proposed algorithms produce better results when compared...

An Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real‐Time Reservoir Operating Rules

Mon, 26 Aug 2019 00:00:00 +0000

Abstract Revenues from hydropower generation often depend on the operator's ability to provide firm power in the presence of uncertain inflows. The primary options available for optimizing revenue are negotiation of a firm power contract before operations begin and adjustment of the reservoir release during operations. Contract and release strategy optimization are closely coupled and most appropriately analyzed with stochastic real‐time control methods. Here we use an ensemble‐based approach to stochastic optimization that provides a convenient way to construct nonparametric revenue probability distributions to explore the implications of uncertainty. The firm power contract is a simplified bilateral fixed price agreement that partially insulates operator and buyer from price fluctuations. The release control laws and firm energy target are jointly optimized to maximize the operator's expected revenue. Revenue probability distributions and related spill performance statistics...

Parallel-In-Time Magnus Integrators

Mon, 19 Aug 2019 00:00:00 +0000

Finding high-redshift strong lenses in DES using convolutional neural networks

Tue, 6 Aug 2019 00:00:00 +0000

We search Dark Energy Survey (DES) Year 3 imaging data for galaxy–galaxy strong gravitational lenses using convolutional neural networks. We generate 250 000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. Using the simulations as a guide, we build a catalogue of 1.1 million DES sources with 1.8 < g − i < 5, 0.6 < g − r < 3, r_mag > 19, g_mag > 20, and i_mag > 18.2. We train two ensembles of neural networks on training sets consisting of simulated lenses, simulated non-lenses, and real sources. We use the neural networks to score images of each of the sources in our catalogue with a value from 0 to 1, and select those with scores greater than a chosen threshold for visual inspection, resulting in a candidate set of 7301 galaxies. During visual inspection, we rate 84 as ‘probably’ or ‘definitely’ lenses. Four of these are previously known lenses or lens candidates....

Study of charmonium production in b-hadron decays and first evidence for the decay Bs0→ϕϕϕ

Mon, 29 Jul 2019 00:00:00 +0000

Using decays to ϕ$$\phi $$-meson pairs, the inclusive production of charmonium states in b$${b} $$-hadron decays is studied with pp collision data corresponding to an integrated luminosity of 3.0fb-1$$3.0 {\,\mathrm{fb}}^{-1} $$, collected by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV. Denoting by BC≡B(b→CX)×B(C→ϕϕ)$${\mathcal {B}} _C \equiv {\mathcal {B}} ( {{b}} \!\rightarrow C X ) \times {\mathcal {B}} ( C\!\rightarrow \phi \phi )$$ the inclusive branching fraction of a b$${{b}} $$ hadron to a charmonium state C that decays into a pair of ϕ$$\phi $$ mesons, ratios RC2C1≡BC1/BC2$$R^{C_1}_{C_2}\equiv {\mathcal {B}} _{C_1} / {\mathcal {B}} _{C_2}$$ are determined as Rηc(1S)χc0=0.147±0.023±0.011$$R^{{\upchi _{{{c}} 0}}}_{{\eta _{{c}}} (1S)} = 0.147 \pm 0.023 \pm 0.011$$, Rηc(1S)χc1=0.073±0.016±0.006$$R^{{\upchi _{{{c}} 1}}}_{{\eta _{{c}}} (1S)} = 0.073 \pm 0.016 \pm 0.006$$, Rηc(1S)χc2=0.081±0.013±0.005$$R^{{\upchi _{{{c}} 2}}}_{{\eta _{{c}}} (1S)} = 0.081...

First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Photometric Pipeline and Light-curve Data Release

Tue, 21 May 2019 00:00:00 +0000

We present griz light curves of 251 SNe Ia from the first 3 years of the Dark Energy Survey Supernova Program’s (DES-SN) spectroscopically classified sample. The photometric pipeline described in this paper produces the calibrated fluxes and associated uncertainties used in the cosmological parameter analysis by employing a scene modeling approach that simultaneously models a variable transient flux and temporally constant host galaxy. We inject artificial point sources onto DECam images to test the accuracy of our photometric method. Upon comparison of input and measured artificial supernova fluxes, we find that flux biases peak at 3 mmag. We require corrections to our photometric uncertainties as a function of host galaxy surface brightness at the transient location, similar to that seen by the DES Difference Imaging Pipeline used to discover transients. The public release of the light curves can be found at https://des.ncsa.illinois.edu/releases/sn.

Soft x-ray ptychography studies of nanoscale magnetic and structural correlations in thin SmCo5 films

Wed, 3 Apr 2019 00:00:00 +0000

High spatial resolution magnetic x-ray spectromicroscopy at x-ray photon energies near the cobalt L3 resonance was applied to probe an amorphous 50 nm thin SmCo5 film prepared by off-axis pulsed laser deposition onto an x-ray transparent 200 nm thin Si3N4 membrane. Alternating gradient magnetometry shows a strong in-plane anisotropy and an only weak perpendicular magnetic anisotropy, which is confirmed by magnetic transmission soft x-ray microscopy images showing over a field of view of 10 μm a primarily stripe-like domain pattern but with local labyrinth-like domains. Soft x-ray ptychography in amplitude and phase contrast was used to identify and characterize local magnetic and structural features over a field of view of 1 μm with a spatial resolution of about 10 nm. There, the magnetic labyrinth domain patterns are accompanied by nanoscale structural inclusions that are primarily located in close proximity to the magnetic domain walls. Our analysis suggests that these inclusions...

The Dark Energy Survey: Data Release 1

Tue, 19 Mar 2019 00:00:00 +0000

We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single-epoch images, co-added images, co-added source catalogs, and associated products and services assembled over the first 3 yr of DES science operations. DES DR1 is based on optical/near-infrared imaging from 345 distinct nights (2013 August to 2016 February) by the Dark Energy Camera mounted on the 4 m Blanco telescope at the Cerro Tololo Inter-American Observatory in Chile. We release data from the DES wide-area survey covering ∼5000 deg2 of the southern Galactic cap in five broad photometric bands, grizY. DES DR1 has a median delivered point-spread function of , r = 0.96, i = 0.88, z = 0.84, and Y = 0.″90 FWHM, a photometric precision of <1% in all bands, and an astrometric precision of 151 . The median co-added catalog depth for a 1.″95 diameter aperture at signal-to-noise ratio (S/N) = 10 is g = 24.33, r = 24.08, i = 23.44, z = 22.69, and Y = 21.44 . DES DR1 includes...

First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters

Tue, 19 Mar 2019 00:00:00 +0000

We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe Ia from the first three years of DES-SN, combined with a low-redshift sample of 122 SNe from the literature. Our “DES-SN3YR” result from these 329 SNe Ia is based on a series of companion analyses and improvements covering SN Ia discovery, spectroscopic selection, photometry, calibration, distance bias corrections, and evaluation of systematic uncertainties. For a flat ΛCDM model we find a matter density . For a flat wCDM model, and combining our SN Ia constraints with those from the cosmic microwave background (CMB), we find a dark energy equation of state , and . For a flat w0waCDM model, and combining probes from SN Ia, CMB and baryon acoustic oscillations, we find and . These results are in agreement with a cosmological constant and with previous...

A fourth-order adaptive mesh refinement algorithm for the multicomponent, reacting compressible Navier–Stokes equations

Tue, 5 Mar 2019 00:00:00 +0000

In this paper, we present a fourth-order in space and time block-structured adaptive mesh refinement algorithm for the compressible multicomponent reacting Navier–Stokes equations. The algorithm uses a finite-volume approach that incorporates a fourth-order discretisation of the convective terms. The time-stepping algorithm is based on a multi-level spectral deferred corrections method that enables explicit treatment of advection and diffusion coupled with an implicit treatment of reactions. The temporal scheme is embedded in a block-structured adaptive mesh refinement algorithm that includes subcycling in time with spectral deferred correction sweeps applied on levels. Here we present the details of the multi-level scheme paying particular attention to the treatment of coarse–fine boundaries required to maintain fourth-order accuracy in time. We then demonstrate the convergence properties of the algorithm on several test cases including both non-reacting and reacting flows. Finally...

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding

Mon, 11 Feb 2019 00:00:00 +0000

BACKGROUND: Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. NEW METHOD: Dictionary learning and sparse coding allow for constructing improved cell representations using IF...

Witnessing eigenstates for quantum simulation of Hamiltonian spectra

Wed, 6 Feb 2019 00:00:00 +0000

The efficient calculation of Hamiltonian spectra, a problem often intractable on classical machines, can find application in many fields, from physics to chemistry. We introduce the concept of an "eigenstate witness" and, through it, provide a new quantum approach that combines variational methods and phase estimation to approximate eigenvalues for both ground and excited states. This protocol is experimentally verified on a programmable silicon quantum photonic chip, a mass-manufacturable platform, which embeds entangled state generation, arbitrary controlled unitary operations, and projective measurements. Both ground and excited states are experimentally found with fidelities >99%, and their eigenvalues are estimated with 32 bits of precision. We also investigate and discuss the scalability of the approach and study its performance through numerical simulations of more complex Hamiltonians. This result shows promising progress toward quantum chemistry on quantum computers.

UPC++: A High-Performance Communication Framework for Asynchronous Computation

Wed, 6 Feb 2019 00:00:00 +0000

UPC++ is a C++ library that supports high-performance computation via an asynchronous communication framework. This paper describes a new incarnation that differs substantially from its predecessor, and we discuss the reasons for our design decisions. We present new design features, including future-based asynchrony management, distributed objects, and generalized Remote Procedure Call (RPC). We show microbenchmark performance results demonstrating that one-sided Remote Memory Access (RMA) in UPC++ is competitive with MPI-3 RMA; on a Cray XC40 UPC++ delivers up to a 25% improvement in the latency of blocking RMA put, and up to a 33% bandwidth improvement in an RMA throughput test. We showcase the benefits of UPC++ with irregular applications through a pair of application motifs, a distributed hash table and a sparse solver component. Our distributed hash table in UPC++ delivers near-linear weak scaling up to 34816 cores of a Cray XC40. Our UPC++ implementation of the sparse...

The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign – I. Overview and classification of candidates selected by two techniques

Tue, 15 Jan 2019 00:00:00 +0000

The primary goals of the STRong lensing Insights into the Dark Energy Survey (STRIDES) collaboration are to measure the dark energy equation of state parameter and the free streaming length of dark matter. To this aim, STRIDES is discovering strongly lensed quasars in the imaging data of the Dark Energy Survey and following them up to measure time delays, high resolution imaging, and spectroscopy sufficient to construct accurate lens models. In this paper, we first present forecasts for STRIDES. Then, we describe the STRIDES classification scheme, and give an overview of the Fall 2016 follow-up campaign. We continue by detailing the results of two selection methods, the outlier selection technique and a morphological algorithm, and presenting lens models of a system that could possibly be a lensed quasar in an unusual configuration. We conclude with the summary statistics of the Fall 2016 campaign. Including searches presented in companion papers (Anguita et al.; Ostrovski et...

COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses

Wed, 12 Dec 2018 00:00:00 +0000

We present time-delay measurements for the new quadruple imaged quasar DES J0408−5354, the first quadruple imaged quasar found in the Dark Energy Survey (DES). Our result is made possible by implementing a new observational strategy using almost daily observations with the MPIA 2.2 m telescope at La Silla observatory and deep exposures reaching a signal-to-noise ratio of about 1000 per quasar image. This data qualityallows us to catch small photometric variations (a few mmag rms) of the quasar, acting on temporal scales much shorter than microlensing, and hence making the time delay measurement very robust against microlensing. In only seven months we very accurately measured one of the time delays in DES J0408−5354: Δ t (AB) = −112.1 ± 2.1 days (1.8%) using only the MPIA 2.2 m data. In combination with data taken with the 1.2 m Euler Swiss telescope, we also measured two delays involving the D component...

Dark Energy Survey Year 1 results: cross-correlation redshifts – methods and systematics characterization

Wed, 12 Dec 2018 00:00:00 +0000

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions...

Dark Energy Survey Year 1 results: Cosmological constraints from cosmic shear

Tue, 11 Dec 2018 00:00:00 +0000

We use 26×106 galaxies from the Dark Energy Survey (DES) Year 1 shape catalogs over 1321 deg2 of the sky to produce the most significant measurement of cosmic shear in a galaxy survey to date. We constrain cosmological parameters in both the flat ΛCDM and the wCDM models, while also varying the neutrino mass density. These results are shown to be robust using two independent shape catalogs, two independent photo-z calibration methods, and two independent analysis pipelines in a blind analysis. We find a 3.5% fractional uncertainty on σ8(Ωm/0.3)0.5=0.782-0.027+0.027 at 68% C.L., which is a factor of 2.5 improvement over the fractional constraining power of our DES Science Verification results. In wCDM, we find a 4.8% fractional uncertainty on σ8(Ωm/0.3)0.5=0.777-0.038+0.036 and a dark energy equation-of-state w=-0.95-0.39+0.33. We find results that are consistent with previous cosmic shear constraints in σ8—Ωm, and we see no evidence for disagreement of our weak lensing data with...

Dark Energy Survey year 1 results: Galaxy-galaxy lensing

Tue, 11 Dec 2018 00:00:00 +0000

We present galaxy-galaxy lensing measurements from 1321 sq. deg. of the Dark Energy Survey (DES) Year 1 (Y1) data. The lens sample consists of a selection of 660,000 red galaxies with high-precision photometric redshifts, known as redMaGiC, split into five tomographic bins in the redshift range 0.15

Denoising Poisson phaseless measurements via orthogonal dictionary learning.

Thu, 1 Nov 2018 00:00:00 +0000

Phaseless diffraction measurements recorded by CCD detectors are often affected by Poisson noise. In this paper, we propose a dictionary learning model by employing patches based sparsity in order to denoise such Poisson phaseless measurements. The model consists of three terms: (i) A representation term by an orthogonal dictionary, (ii) an L⁰ pseudo norm of the coefficient matrix, and (iii) a Kullback-Leibler divergence term to fit phaseless Poisson data. Fast alternating minimization method (AMM) and proximal alternating linearized minimization (PALM) are adopted to solve the proposed model, and especially the theoretical guarantee of the convergence of PALM is provided. The subproblems for these two algorithms both have fast solvers, and indeed, the solutions for the sparse coding and dictionary updating both have closed forms due to the orthogonality of learned dictionaries. Numerical experiments for phase retrieval using coded diffraction and ptychographic patterns...

Study of ψ(2S) production and cold nuclear matter effects in pPb collisions at sNN=5 TeV