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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Optical phase conjugation in backward Raman amplification

Compression of an intense laser pulse using backward Raman amplification (BRA) in plasma, followed by vacuum focusing to a small spot size, can produce unprecedented ultrarelativistic laser intensities. The plasma density inhomogeneity during BRA, however, causes laser phase and amplitude distortions, limiting the pulse focusability. To solve the issue of distortion, we investigate the use of optical phase conjugation as the seed pulse for BRA. We show that the phase conjugated laser pulses can retain focusability in the nonlinear pump depletion regime of BRA, but not so easily in the linear amplification regime. This somewhat counterintuitive result is because the nonlinear pump depletion regime features a shorter amplification distance, and hence less phase distortion due to wave–wave interaction, than the linear amplification regime.

Jia, Qing↗

Efficient backward x-ray emission in a finite-length plasma irradiated by a laser pulse of picosecond duration

Motivated by experiments employing picosecond-long, kilojoule laser pulses, we examined x-ray emission in a finite-length underdense plasma irradiated by such a pulse using two-dimensional particle-in-cell simulations. We found that, in addition to the expected forward emission, the plasma also efficiently emits in the backward direction. Our simulations reveal that the backward emission occurs when the laser exits the plasma. The longitudinal plasma electric field generated by the laser at the density down-ramp turns around some of the laser-accelerated electrons and re-accelerates them in the backward direction. As the electrons collide with the laser, they emit hard x rays. The energy conversion efficiency is comparable to that for the forward emission, but the effective source size is smaller. We show that the picosecond laser duration is required for achieving a spatial overlap between the laser and the backward energetic electrons. At peak laser intensity of 1.4×1020 W/cm2, backward-emitted photons (energies above 100 keV and 10° divergence angle) account for 2×10−5 of the incident laser energy. This conversion efficiency is three times higher than that for similarly selected forward-emitted photons. The source size of the backward photons (5 μm) is three times smaller than the source size of the forward photons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation studies related to the particle identification by the forward and backward RICH detectors at Electron Ion Collider

The Electron-Ion collider (EIC) will be the ultimate facility to study the dynamics played by colored quarks and gluons in the phenomenology of nucleons and nuclei, described by Quantum Chromodynamics. The physics programs will greatly rely on efficient particle identification (PID) in both the forward and the backward regions. The forward and the backward RICHes of the EIC have to be able to cover wide acceptance and momentum ranges; in the forward region a dual radiator RICH (dRICH) is foreseen and in the backward region a proximity-focusing RICH can be foreseen to be employed. The geometry and the performance studies of the dRICH have been performed as prescribed in the EIC Yellow Report using the ATHENA software framework. Furthermore, this part of our work reports the effort following the call for EIC detector proposal and the studies related to the forward and the backward RICH performance. In the forward region, the dRICH performance showed a pion- kaon separation from around 1 GeV/c to 50 GeV/c at a three sigma level; the proximity focusing RICH (pfRICH) foreseen for the backward region can reach three sigma separation up to 3 GeV/c for e/$π$ and up to 10 GeV/c for $π$/K mass hypotheses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Kernel learning backward SDE filter for data assimilation

In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of forward backward stochastic differential equations is used to propagate the state of the target dynamical model, and Bayesian inference is applied to incorporate the observational information. Further, to characterize the dynamical model in the entire state space, we introduce a kernel learning method to learn a continuous global approximation for the conditional probability density function of the target state by using discrete approximated density values as training data. Numerical experiments demonstrate that the kernel learning backward SDE is highly effective.

97 MATHEMATICS AND COMPUTING↗

Physics-Informed Neural Network Method for Forward and Backward Advection-Dispersion Equations

Advection-dispersion equations (ADEs) are commonly used to describe transport phenomena in porous media. Even though mature discretization-based numerical methods for ADEs exist, some challenges still remain, especially when it comes to solving advection-dominated forward ADEs and diffusion-dominated backward ADEs. The latter problem usually arises in the source identification context and leads to numerically unstable grid-based solutions that require a form of regularization or should be treated as an inverse problem that is computationally more expensive because it requires solving the forward problem multiple times. In this study, we propose a discretization-free approach based on the physics-informed neural network (PINN) method for solving coupled ADE and Darcy flow equations with space-dependent hydraulic conductivity. In this approach, the hydraulic conductivity, hydraulic head, and concentration fields are approximated with deep neural networks (DNNs). We assume that the conductivity field is given by its values on a grid, and we use these values to train the conductivity DNN. The head and concentration DNNs are trained by minimizing the residuals of the flow equation and ADE and using the initial and boundary conditions as additional constraints. The PINN method is applied to one- and two-dimensional forward ADE problems, where its performance for various P\'{e}clet numbers ($Pe$) is compared with the analytical and numerical solutions. We find that the PINN method is accurate with errors of less than 1\% and outperforms some conventional discretization-based methods for $Pe$ larger that 100. Next, we demonstrate that the PINN method remains accurate for the backward ADEs, with the relative errors in most cases staying under 5\% compared to the reference concentration field. Finally, we show that when available, the concentration measurements can be easily incorporated in the PINN method and significantly improve (by more than 50\% in the considered cases) the accuracy of the PINN solution of the backward ADE.

He, Qizhi↗

Progress and opportunities in backward angle (u-channel) physics

Backward angle (u-channel) scattering provides complementary information for studies of hadron spectroscopy and structure, but has been less comprehensively studied than the corresponding forward angle case. As a result, the physics of u-channel scattering poses a range of new experimental and theoretical opportunities and questions. We summarize recent progress in measuring and understanding high energy reactions with baryon charge exchange in the u-channel, as discussed in the first Backward angle (u-channel) Physics Workshop. In particular, we discuss backward angle measurements and their theoretical description via both hadronic models and the collinear factorization approach, and discuss planned future measurements of u-channel physics. Finally, we propose outstanding questions and challenges for u-channel physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Tracer Particles for Core-collapse Supernova Nucleosynthesis: The Advantages of Moving Backward

Abstract After decades, the theoretical study of core-collapse supernova explosions is moving from parameterized, spherically symmetric models to increasingly realistic multidimensional simulations. However, obtaining nucleosynthesis yields based on such multidimensional core-collapse supernova simulations is not straightforward. Frequently, tracer particles are employed. Tracer particles may be tracked in situ during the simulation, but often they are reconstructed in a post-processing step based on the information saved during the hydrodynamic simulation. Reconstruction can be done in a number of ways, and here we compare the approaches of backward and forward integration of the equations of motion to the results based on inline particle trajectories. We find that both methods agree reasonably well with the inline results for isotopes for which a large number of particles contribute. However, for rarer isotopes that are produced only by a small number of particle trajectories, deviations can be large. For our setup, we find that backward integration leads to better agreement with the inline particles by more accurately reproducing the conditions following freeze-out from nuclear statistical equilibrium, because the establishment of nuclear statistical equilibrium erases the need for detailed trajectories at earlier times. Based on our results, if inline tracers are unavailable, we recommend backward reconstruction to the point when nuclear statistical equilibrium was last applied, with an interval between simulation snapshots of at most 1 ms for nucleosynthesis post-processing.

79 ASTRONOMY AND ASTROPHYSICS↗

Bulk reconstruction and non-isometry in the backwards-forwards holographic black hole map

The backwards-forwards map, introduced as a generalization of the non-isometric holographic maps of the black hole interior of Akers, Engelhardt, Harlow, Penington, and Vardhan to include non-trivial dynamics in the effective description, has two possible formulations differing in when the post-selection is performed. While these two forms are equivalent on the set of dynamically generated states — states formed from unitary time evolution acting on well-defined initial configurations of infalling matter — they differ on the generic set of states necessary to describe the apparent world of the infalling observer. We show that while both versions successfully reproduce the Page curve, the version involving post-selection as the final step, dubbed the backwards-forwards-post-selection (BFP) map, has the desirable properties of being non-isometric but isometric on average and providing state-dependent reconstruction of bulk operators, while the other version does not. Thus the BFP map is a suitable non-isometric code describing the black hole interior including interior interactions.

3-D Image Reconstruction↗

The CLAS12 Backward Angle Neutron Detector (BAND)

The Backward Angle Neutron Detector (BAND) of CLAS12 detects neutrons emitted at backward angles of 155° to 175°, with momenta between 200 and 600 MeV$/c_0$. It is positioned 3-m upstream of the target, consists of 18 rows and 5 layers of 7.2-cm by 7.2-cm scintillator bars, and read out on both ends by PMTs to measure time and energy deposition in the scintillator layers. Between the target and BAND there is a 2-cm thick lead wall followed by a 2-cm veto layer to suppress gammas and reject charged particles. This paper discusses the component-selection tests and the detector assembly. Timing calibrations (including offsets and time-walk) were performed using a novel pulsed-laser calibration system, resulting in time resolutions better than 250 ps (150 ps) for energy depositions above 2 MeV (5 MeV). Cosmic rays and a variety of radioactive sources were used to calibration the energy response of the detector. Scintillator bar attenuation lengths were measured. We report the time resolution results in a neutron momentum reconstruction resolution, $δp/p$ < 1.5% for neutron momentum 200 ≤ $p$ ≤ 600 MeV/c. Final performance of the BAND with CLAS12 is shown, including electron–neutral particle timing spectra and a discussion of the off-time neutral contamination as a function of energy deposition threshold.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurements of azimuthal anisotropies at forward and backward rapidity with muons in high-multiplicity p–Pb collisions at $\sqrt{s_{NN}} = 8.16$ TeV

The study of the azimuthal anisotropy of inclusive muons produced in p–Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV, using the ALICE detector at the LHC is reported. The measurement of the second-order Fourier coefficient of the particle azimuthal distribution, v 2 , is performed as a function of transverse momentum p T in the 0–20% high-multiplicity interval at both forward (2.03 < y CMS < 3.53) and backward (-4.46 < y CMS < -2.96) rapidities over a wide pT range, 0.5 < p T < 10 GeV/c, in which a dominant contribution of muons from heavy-flavour hadron decays is expected at p T > 2 GeV/c. The v 2 coefficient of inclusive muons is extracted using two different techniques, namely two-particle cumulants, used for the first time for heavy-flavour measurements, and forward–central two-particle correlations. Both techniques give compatible results. A positive v 2 is measured at both forward and backward rapidities with a significance larger than 4.7σ and 7.6σ, respectively, in the interval 2 < p T < 6 GeV/c. Comparisons with previous measurements in p–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV, and with AMPT and CGC-based theoretical calculations are discussed. The findings impose new constraints on the theoretical interpretations of the origin of the collective behaviour in small collision systems

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multiplicity dependent 𝐽/𝜓 and 𝜓⁡(2⁢𝑆) production at forward and backward rapidity in 𝑝 + 𝑝 collisions at $\sqrt{𝑠}$ = 200 GeV

Recent measurements of 𝐽/𝜓 production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced 𝐽/𝜓 production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We present the first study of potential autocorrelations at RHIC energies and forward and backward rapidity of self-normalized 𝐽/𝜓 yields and 𝜓⁡(2⁢𝑆) to 𝐽/𝜓 ratio, as a function of self-normalized multiplicity in 𝑝 + 𝑝 collisions. In addition, detailed pythia studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by pythia calculations that include MPI effects. The forward and backward 𝜓⁡(2⁢𝑆) to 𝐽/𝜓 ratio is found to be less dependent on the charged-particle multiplicity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nuclear Modification Factor of Neutral Pions in the Forward and Backward Regions in p - Pb Collisions

The nuclear modification factor of neutral pions is measured in proton-lead collisions collected at a center-of-mass energy per nucleon of 8.16 TeV with the LHCb detector. The π 0 production cross section is measured differentially in transverse momentum (p T ) for 1.5 < p Τ < 10.0 GeV and in center-of-mass pseudorapidity (η c.m. ) regions 2.5 < η c.m. < 3.5 (forward) and -4.0 < η c.m .< -3.0 (backward) defined relative to the proton beam direction. The forward measurement shows a sizable suppression of π 0 production, while the backward measurement shows the first evidence of π 0 enhancement in proton-lead collisions at the LHC. Together, these measurements provide precise constraints on models of nuclear structure and particle production in high-energy nuclear collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive Angular Quadrature Scheme for a backwards-in-time Method of Characteristics Solution to the Radiative Transfer Equation [Slides]

Radiative transfer/radiation transport are important problems to solve in astrophysics and high energy density physics. Various methods exist to solve radiation transport, such as Monte Carlo (MC), Discrete Ordinates (S N ), Method of Characteristics (MOC), and the spherical harmonics (P N ) method. Method of Characteristics requires “launching” of rays in discrete directions. Unresolved details of angular mesh create ray effects and can miss sources in the domain. Ray effects can lead to unphysical “stepping” in solution and incorrect energy deposition. Adaptive quadrature schemes can be used to detect and mitigate these effects. The Method of Characteristics (MOC) is a common method for solving hyperbolic PDEs in radiation transport and supersonic flow problems. Generally in MOC for radiation transport, virtual particles are tracked from birth to the end of a timestep. This requires interpolation to go from final location to cell averaged or corner values of angular intensity. Backwards-in-Time (BIT) particle tracking avoids this by prescribing the final position of the virtual particle at the cell nodes/corners. Angular intensities are computed at time k + 1 by launching ray back to previous timestep(s), or t = 0. Scheme allows solution to be computed as the characteristic ray is traced backwards in time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Simultaneous Forward-Backward Prony Estimation

Power system dynamic stability can be evaluated through the analysis of transient oscillations that occur following significant system events. One of the earliest methods for this type of study is Prony analysis, which estimates the system's electromechanical modes. While previous studies have highlighted advantages of performing Prony analysis on data in the forward and backward directions, the proposed method does so simultaneously. As a result, signal poles corresponding to electromechanical modes can be distinguished from spurious poles more reliably. The method also produces a single mode estimate, where independent application in the forward and backward directions would produce two estimates for each mode. The method is validated using simulated and measured power system data.

Follum, James D.↗

A backward SDE method for uncertainty quantification in deep learning

Here, we develop a backward stochastic differential equation based probabilistic machine learning method, which formulates a class of stochastic neural networks as a stochastic optimal control problem. An efficient stochastic gradient descent algorithm is introduced with the gradient computed through a backward stochastic differential equation. Convergence analysis for stochastic gradient descent optimization and numerical experiments for applications of stochastic neural networks are carried out to validate our methodology in both theory and performance.

97 MATHEMATICS AND COMPUTING↗

On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals

We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in contrast to the work (Daubechies et al., Pure Appl. Math. 57(11), 1413–1457, 2004), where the single vector signal can be infinite-dimensional, and (Fornasier and Rauhut, SIAM J. Numer. Anal. 46(2), 577613, 2008), which extends the aforementioned work to the joint sparse recovery of finite number of infinite-dimensional vectors. In our case, to take account of the joint sparsity and promote the coupling of nonvanishing components, we employ a convex relaxation approach with mixed norm penalty ℓ 2,1 . This paper discusses the computation of the solutions of linear inverse problems with such relaxation by a forward-backward splitting algorithm. However, since the solution matrix possesses infinitely many columns, the arguments of Daubechies et al. (Pure Appl. Math. 57(11), 1413–1457, 2004) no longer apply. As such, we establish new strong convergence results for the algorithm, in particular when the set of jointly sparse vectors is infinite.

97 MATHEMATICS AND COMPUTING↗