Monitoring the Evolution of Relative Product Populations at Early Times during a Photochemical Reaction
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Quasinormal modes describe the return to equilibrium of a perturbed system, in particular the ringdown phase of a black hole merger. But as globally-defined quantities, the quasinormal spectrum can be highly sensitive to global structure, including distant small perturbations to the potential. In what sense are quasinormal modes a property of the resulting black hole? We explore this question for the linearized perturbation equation with two potentials having disjoint bounded support. We give a composition law for the Wronskian that determines the quasinormal frequencies of the combined system. We show that over short time scales the evolution is governed by the quasinormal frequencies of the individual potentials, while the sensitivity to global structure can be understood in terms of echoes. We introduce an echo expansion of the Green’s function and show that, as expected on general grounds, at any finite time causality limits the number of echoes that can contribute. We illustrate our results with the soluble example of a pair of -function potentials. We explicate the causal structure of the Green’s function, demonstrating under what conditions two very different quasinormal spectra give rise to very similar ringdown waveforms.
We report the magneto-Rayleigh-Taylor instability (MRTI) plays an essential role in astrophysical systems and in magneto-inertial fusion, where it is known to be an important degradation mechanism of confinement and target performance. In this Letter, we show for the first time experimental evidence of mode mixing and the onset of an inverse-cascade process resulting from the nonlinear coupling of two discrete preseeded axial modes (400- and 550 - μm wavelengths) on an Al liner that is magnetically imploded using the 20-MA, 100-ns rise-time Z Machine at Sandia National Laboratories. Four radiographs captured the temporal evolution of the MRTI. We introduce a novel unfold technique to analyze the experimental radiographs and compare the results to simulations and to a weakly nonlinear model. We find good quantitative agreement with simulations using the radiation magnetohydrodynamics code hydra. Spectral analysis of the MRTI time evolution obtained from the simulations shows evidence of harmonic generation, mode coupling, and the onset of an inverse-cascade process. The experiments provide a benchmark for future work on the MRTI and motivate the development of new analytical theories to better understand this instability.
Microalgae are increasingly used to generate a wide range of commercial products, and there is growing evidence that microalgae-based products can be produced sustainably. However, industrial production of microalgal biomass is not as developed as other biomanufacturing platform technologies. In addition, results of bench-scale research often fail to translate to large-scale or mass production systems. This disconnect may result from trait drift and evolution occurring, through time, in response to unique drivers in each environment, such as cultivation regimes, weather, and pests. Moreover, outdoor and indoor cultivation of microalgae has the potential to impose negative selection pressures, which makes the maintenance of desired traits a challenge. In this context, this review sheds the light on our current understanding of trait drift and evolution in microalgae. Here, we delineate the basics of phenotype plasticity and evolution, with a focus on how microalgae respond under various conditions. In addition, we review techniques that exploit phenotypic plasticity and evolution for strain improvement in view of industrial commercial applications, highlighting associated advantages and shortcomings. Finally, we suggest future research directions and recommendations to overcome unwanted trait drift and evolution in microalgae cultivation.
Structural materials used in the next generation nuclear reactors or other advanced energy systems are often required to withstand higher operating temperatures for a longer service life. Alloy 709 (A709), a Nb-containing and N-stabilized Fe-25Ni-20Cr austenitic stainless steel, has been recommended for high-temperature reactor constructions due to the better performance over the baseline Type 316H stainless steel. Here, in the current manuscript, for the first time, the microstructure evolution and tensile behavior of an A709 made by laser powder bed fusion (LPBF) is discussed. The as deposited and heat treated LPBF alloys are compared with a reference wrought alloy. Owing to the chemical segregation and a higher number of dislocations, the LPBF materials show a significantly higher density of precipitates formed during high temperature treatments when compared to the wrought samples. This is reflected when looking at the tensile properties, both at room and elevated temperatures, where LPBF samples show higher strengths compared to wrought materials.
We aim to unravel the interplay between bars, star formation (SF), and active galactic nuclei (AGNs) in barred galaxies. To this end, we utilize the SDSS DR12 to select a sample of nearby (0.02 < z < 0.06) disk galaxies that are suitable for bar examination (M r < –20.12 and inclination ≲53°). We identify 3662 barred galaxies and measure the length and axis ratio of each bar. We invent new bar parameters that mitigate the stellar and bulge mass biases and show, for the first time, that the evolution of non-AGN and AGN-hosting barred galaxies should be tracked using different bar parameters: the bar length for non-AGN galaxies and the bar axis ratio for AGN-hosting galaxies. Our analysis confirms that barred galaxies have a higher specific SF rate than unbarred control galaxies. Moreover, we find a positive correlation of bar length with both the SF enhancement and the centrally star-forming galaxy fraction, indicating the interconnectivity of bars and SF through the bar-driven gas inflow. We also find that, while the AGN fraction of barred galaxies is the same as that of the unbarred control sample, galaxies hosting more massive black holes (BHs) have rounder (i.e., higher axis ratio) bars, implying that the bar is not a cause of AGN activity; rather, AGNs appear to regulate bars. Our findings corroborate theoretical predictions that bars in non-AGN galaxies grow in length, and bars in AGN-hosting galaxies become rounder as BHs grow and eventually get destroyed.
Abstract Quantum annealing (QA) is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare ground state and a problem Hamiltonian whose ground state encodes solutions to an optimization problem. The standard implementation relies on the evolution being adiabatic: keeping the system in the instantaneous ground state with high probability and requiring a time scale inversely related to the minimum energy gap between the instantaneous ground and excited states. However, adiabatic evolution can lead to evolution times that scale exponentially with the system size, even for computationally simple problems. Here, we study whether non-adiabatic evolutions with optimized annealing schedules can bypass this exponential slowdown for one such class of problems called the frustrated ring model. For sufficiently optimized annealing schedules and system sizes of up to 39 qubits, we provide numerical evidence that we can avoid the exponential slowdown. Our work highlights the potential of highly-controllable QA to circumvent bottlenecks associated with the standard implementation of QA.
Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.
Abstract Low gain avalanche detectors (LGADs) deliver excellent timing resolution, which can mitigate mis-assignment of vertices associated with pileup at the High Luminosity LHC and other future hadron colliders. The most highly irradiated LGADs will be subject to 2.5 × 10 15 n eq cm -2 of hadronic fluence during HL-LHC operation; their performance must tolerate this. Hamamatsu Photonics K.K. and Fondazione Bruno Kessler LGADs have been irradiated with 400 and 500 MeV protons respectively in several steps up to 1.5 × 10 15 n eq cm -2 . Measurements of the acceptor removal constants of the gain layers, evolution of the timing resolution and charge collection with damage, and inter-channel isolation characteristics, for a variety of design options, are presented here.
Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.
We present a wholly self-consistent, complete cyclic bouncing cosmology based on components drawn from string theory and constructed in a way that is under perturbative control throughout (e.g., with temperature much less than the string scale and string coupling g s ≪ 1 at all times). The cyclic evolution is governed by standard dilaton-gravity in (3+1)-dimensions with a perturbatively generated potential and a coupling between the dilaton and a second field that becomes massless at ϕ = ϕ ESP , resulting in an enhanced symmetry point (ESP) that prevents the dilaton from running all the way to zero coupling. A central role is played by instant folded strings (IFSs) — fundamental strings with the unusual property of being much lighter than the string mass while extending far beyond the string length, and violating the Null Energy Condition (NEC). IFSs are produced classically when the string coupling grows with time, which occurs at two critical points in each cycle. In turn, they fulfill a dual function: Enabling cosmological bounces and initiating transient epochs of dark-energy domination that naturally transition into slow contraction. The resulting cosmology eliminates the cosmic singularity and multiverse problems of big bang inflationary models and robustly predicts time-varying IFS-induced dark energy and the absence of primordial B-mode polarization in the cosmic microwave background.
This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.
We present a wholly self-consistent, complete cyclic bouncing cosmology based on components drawn from string theory and constructed in a way that is under perturbative control throughout (e.g., with temperature much less than the string scale and string coupling $g_s \ll 1$ at all times). The cyclic evolution is governed by standard dilaton-gravity in $(3+1)$-dimensions with a perturbatively generated potential and a coupling between the dilaton and a second field that becomes massless at $ϕ= ϕ_{ESP}$, resulting in an enhanced symmetry point (ESP) that prevents the dilaton from running all the way to zero coupling. A central role is played by instant folded strings (IFSs) - fundamental strings with the unusual property of being much lighter than the string mass while extending far beyond the string length, and violating the Null Energy Condition (NEC). IFSs are produced classically when the string coupling grows with time, which occurs at two critical points in each cycle. In turn, they fulfill a dual function: enabling cosmological bounces and initiating transient epochs of dark-energy domination that naturally transition into slow contraction. The resulting cosmology eliminates the cosmic singularity and multiverse problems of big bang inflationary models and robustly predicts time-varying IFS-induced dark energy and the absence of primordial B-mode polarization in the cosmic microwave background.
Electron correlations play a dominant role in the charge dynamics of the cuprates. We use resonant inelastic X-ray scattering (RIXS) to track the doping dependence of the collective charge excitations in electron doped La 2-x Ce x CuO 4 (LCCO). From the resonant energy dependence and the out-of-plane momentum dependence, the charge excitations are identified as three-dimensional (3D) plasmons, which reflect the nature of the electronic structure and Coulomb repulsion on both short and long lengthscales. With increasing electron doping, the plasmon excitations increase monotonically in energy, a consequence of the electron correlation effect on electron structure near the Fermi surface (FS). Importantly, the plasmon excitations evolve from a broad feature into a well-defined peak with much increased life time, revealing the evolution of the electrons from incoherent states to coherent quasi-particles near the FS. Such evolution marks the reduction of the short-range electronic correlation, and thus the softening of the Mottness of the system with increasing electron doping.
We report peridynamics is a relatively new field in continuum mechanics that has developed over the past 20 years. This paper studies the evolution of collaborations in the field of peridynamics since its inception using social network analysis. For this purpose, we construct a network for each year from 2000 to 2019 describing co-authorship between scientists in peridynamics. In these networks, each node represents a scientist and each link connects two co-authoring scientists with a link weight representing the frequency and strength of their collaboration; each network as a whole can be thought of as a graph representation of the peridynamics community for the given year. By constructing a network for each year, we are able to analyze the evolution of the network in time and discuss the implications of this evolution for the peridynamics community. Our study demonstrates that the peridynamics community has been growing exponentially in size in recent years. Centrality metrics are also used to identify the most collaborative scientists in the community. Moreover, we compute link recommendations based on both elevating a scientist’s position in the network with respect to certain centrality metrics or closing structural holes in the network identified with persistent homology. We further extend the analysis to higher-order networks whose nodes represent groups of scientists in the community and whose links connect collaborating groups. In some sense, our work studies the past, present, and future of the peridynamics community.
ABSTRACT Cross-correlations between the lensing of the cosmic microwave background (CMB) and other tracers of large-scale structure provide a unique way to reconstruct the growth of dark matter, break degeneracies between cosmology and galaxy physics, and test theories of modified gravity. We detect a cross-correlation between Dark Energy Spectroscopic Instrument (DESI)-like luminous red galaxies (LRGs) selected from DECam Legacy Survey imaging and CMB lensing maps reconstructed with the Planck satellite at a significance of S/N = 27.2 over scales ℓmin = 30, ℓmax = 1000. To correct for magnification bias, we determine the slope of the LRG cumulative magnitude function at the faint limit as s = 0.999 ± 0.015, and find corresponding corrections of the order of a few per cent for $C^{\kappa g}_{\ell }, C^{gg}_{\ell }$ across the scales of interest. We fit the large-scale galaxy bias at the effective redshift of the cross-correlation zeff ≈ 0.68 using two different bias evolution agnostic models: a HaloFit times linear bias model where the bias evolution is folded into the clustering-based estimation of the redshift kernel, and a Lagrangian perturbation theory model of the clustering evaluated at zeff. We also determine the error on the bias from uncertainty in the redshift distribution; within this error, the two methods show excellent agreement with each other and with DESI survey expectations.
The evolution from gas-phase oxidation to nanoparticle and agglomerate formation was studied in nanosecond laser-produced plasmas of a multi-principal element alloy target in air. Here gas-phase oxidation of plasma species was monitored in situ via optical emission spectroscopy, while a custom-built single particle mass spectrometer was used to measure size and compositions of agglomerated nanoparticles formed in laser ablation plumes. Ex situ analysis employing transmission electron microscopy was used to study nanoparticle morphology, crystal structure, and element distribution at the nanoscale. Emission spectra indicate that gas-phase oxidation of elements in the alloy target are formed at varying times during plume evolution, and mass spectrometry results indicate fractal agglomerates contain all principal alloying elements and their oxides. Finally, electron microscopy characterization illustrates that these agglomerates consist of multiple material types: sub-10 nm diameter amorphous, multi-element nanoparticles, ≈10–30 nm diameter Ti-rich crystalline oxide nanoparticles, and ejected base material. Results highlight that the multi-component target composition impacts molecular formation in the gas phase and the morphology, composition, and structure of nanoparticles and agglomerates formed.
Laser-produced plasma coupled with optical emission spectroscopy (OES) is a promising technique for detecting certain isotopes, with unique capabilities such as standoff and rapid detection and minimal to no sample preparation requirements. The key figure-of-merit for isotopic analysis using optical spectroscopy tools is the linewidth relative to the isotope shift. Although the isotopes of hydrogen (1H, 2H, and 3H) possess large isotopic shifts (1H–2H ≈ 180 pm, 1H–3H ≈ 240 pm), being a light element, the H transitions are susceptible to various broadening mechanisms in the plasma environment. One of the critical parameters that influence the linewidth of a transition in an LPP is the incident laser energy. In the present study, we evaluated the role of laser energy on plume expansion dynamics, deuterium emission intensity, and linewidth in a nanosecond laser-produced Zircaloy-4 plasma. The changes in 2Hα emission intensity and linewidth were investigated for varying laser fluence and time after plasma onset. Spatially resolved and spatially integrated OES were performed and compared to investigate the emission spectral features and linewidth of 2Hα. Monochromatic two-dimensional time-resolved imaging was also performed to understand the morphology of the deuterium and protium emission relative to all species in the plume. Our results showed that 1Hα and 2Hα emissions predominantly occur closer to the target. Measurements of 2Hα linewidth approached similar values at later times of plasma evolution regardless of the laser energy. The linewidths of the 2Hα transition showed insignificant differences between spatially resolved and spatially integrated measurements.