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Here, we show that a recently conjectured form for perturbative supersymmetric partition functions on spheres of general dimension d is consistent with the at space limit of 6-dimensional N = 1 super Yang-Mills. We also show that the partition functions for N = 1 8- and 9-dimensional theories are consistent with their known at space limits.
We analyze quantum fluctuations around black hole solutions to the Jackiw-Teitelboim model. We use harmonic analysis on Euclidean AdS 2 to show that the logarithmic corrections to the partition function are determined entirely by quadratic holomorphic differentials, even when conformal symmetry is broken and harmonic modes are no longer true zero modes. Our quantum-corrected partition function agrees precisely with the SYK result. We argue that our effective quantum field theory methods and results generalize to other theories of two-dimensional dilaton gravity.
Abstract We consider the ensemble average of two dimensional symmetric product orbifold CFTs Sym N (𝕋 D ) over the Narain moduli space. We argue for a bulk dual given byNcopies of an abelian Chern-Simons theory coupled to topological gravity, endowed with a discrete gauge symmetry exchanging theNcopies. As a check of this proposal, we calculate the ensemble average of various partition and correlation functions of the symmetric product orbifold theory and compare the resulting expressions to gauge theory quantities in the bulk. We comment on the ensemble average of the tensionless string partition function on AdS 3 × S 3 × 𝕋 4 by considering the specific case ofD= 4 with the addition of supersymmetry.
We use localization techniques to study several duality proposals for supersymmetric gauge theories in three dimensions reminiscent of Seiberg duality. We compare the partition functions of dual theories deformed by real mass terms and FI parameters. We find that Seiberg-like duality for N = 3 Chern-Simons gauge theories proposed by Giveon and Kutasov holds on the level of partition functions and is closely related to level-rank duality in pure Chern-Simons theory. We also clarify the relationship between the Giveon-Kutasov duality and a duality in theories of fractional M2 branes and propose a generalization of the latter. Our analysis also confirms previously known results concerning decoupled free sectors in N = 4 gauge theories realized by monopole operators.
We discuss ensemble averages of two-dimensional conformal field theories associated with an arbitrary indefinite lattice with integral quadratic form Q. We provide evidence that the holographic dual after the ensemble average is the three-dimensional Abelian Chern-Simons theory with kinetic term determined by Q. The resulting partition function can be written as a modular form, expressed as a sum over the partition functions of Chern-Simons theories on lens spaces. For odd lattices, the dual bulk theory is a spin Chern-Simons theory, and we identify several novel phenomena in this case. We also discuss the holographic duality prior to averaging in terms of Maxwell-Chern-Simons theories.
In this paper we study supersymmetric co-dimension 2 and 4 defects in the compactification of the 6d (2, 0) theory of type A N-1 on a 3-manifold M . The so-called 3d-3d correspondence is a relation between complexified Chern-Simons theory (with gauge group SL(N,C) ) on M and a 3d N=2 theory T N [M ]. We study this correspondence in the presence of supersymmetric defects, which are knots/links inside the 3-manifold. Our study employs a number of different methods: state-integral models for complex Chern-Simons theory, cluster algebra techniques, domain wall theory T [SU(N )], 5d N=2 SYM, and also supergravity analysis through holography. These methods are complementary and we find agreement between them. In some cases the results lead to highly non-trivial predictions on the partition function. Our discussion includes a general expression for the cluster partition function, which can be used to compute in the presence of maximal and certain class of non-maximal punctures when N > 2. We also highlight the non-Abelian description of the 3d N=2 T N [M ] theory with defect included, when such a description is available. This paper is a companion to our shorter paper, which summarizes our main results.
We investigate the S 3 free energy of N = 3 Chern-Simons-matter quiver gauge theories with gauge group U(N) r (r ≥ 2) where the sum of Chern-Simons levels does not vanish, beyond the leading order in the large-N limit. We take two different approaches to explore the sub-leading structures of the free energy. First we evaluate the matrix integral for the partition function in the ’t Hooft limit using a saddle point approximation. Second we use an ideal Fermi-gas model to compute the same partition function, but in the limit of fixed Chern-Simons levels. The resulting expressions for the free energy F = – log Z are then compared in the overlapping parameter regime. The Fermi-gas approach also hints at a universal 1/6 log N correction to the free energy. Since the quiver gauge theories we consider are dual to massive Type IIA theory, we expect the sub-leading correction of the planar free energy in the large ’t Hooft parameter limit to match higher-derivative corrections to the tree-level holographic dual free energy, which have not yet been fully investigated.
Abstract Isotopic ratios of radioxenons sampled in the atmosphere or subsurface can be used to verify the occurrence of an underground nuclear explosion (UNE). Differences in the half-lives of radioactive xenon precursors and their decay-chain networks produce different time-dependent concentration profiles of xenon isotopes allowing isotopic ratios to be used for tracking UNE histories including estimating the time of detonation. In this study, we explore the potential effects of post-detonation cavity processes: precipitation of iodine precursors, gas seepage, and prompt venting on radioxenon isotopic evolution which influences UNE histories. Simplified analytical models and closed-form solutions yielding a potentially idealized radioactive decay/ingrowth chain in a closed and well-mixed system typically have limited application by not including the partitioning of the radionuclide inventory between a gas phase and rock melt created by the detonation and by ignoring gas transport from the cavity to host rock or ground surface. In reality, either subsurface transport or prompt release that is principally responsible for gas signatures violates the closed-system (or batch-mode) assumption. A closed-form solution representing time-dependent source-term activities is extended by considering the cavity partitioning process, slow seepage, and/or prompt release of gases from the cavity and applied to realistic systems.
We construct here a Borcherds–Kac–Moody (BKM) superalgebra on which the Conway group \(\hbox {Co}_0\) acts faithfully. We show that the BKM algebra is generated by the physical states (BRST cohomology classes) in a chiral superstring theory. Furthermore, we use this construction to produce denominator identities for the chiral partition functions of the Conway module \(V^{s\natural }\) , a supersymmetric \(c=12\) chiral conformal field theory whose (twisted) partition functions enjoy moonshine properties and which has automorphism group isomorphic to \(\hbox {Co}_0\) . In particular, these functions satisfy a genus zero property analogous to that of monstrous moonshine. Finally, we suggest how one may promote the denominators to spacetime BPS indices in type II string theory, which might thus furnish a physical explanation of the genus zero property of Conway moonshine.
Remote sensing estimation of evapotranspiration (ET) directly quantifies plant water consumption and provides essential information for irrigation scheduling, which is a pressing need for California vineyards as extreme droughts become more frequent. Many ET models take satellite-derived Leaf Area Index (LAI) as a major input, but how uncertainties of LAI estimations propagate to ET and the partitioning between evaporation and transpiration is poorly understood. Here we assessed six satellite-based LAI estimation approaches using Landsat and Sentinel-2 images against ground measurements from four vineyards in California and evaluated ET sensitivity to LAI in the thermal-based two-source energy balance (TSEB) model. We found that radiative transfer modeling-based approaches predicted low to medium LAI well, but they significantly underestimated high LAI in highly clumped vine canopies (RMSE ~ 0.97 to 1.27). Cubist regression models trained with ground LAI measurements from all vineyards achieved high accuracy (RMSE ~ 0.3 to 0.48), but these empirical models did not generalize well between sites. Red edge bands and the related vegetation index (VI) from the Sentinel-2 satellite contain complementary information of LAI to VIs based on near-infrared and red bands. TSEB ET was more sensitive to positive LAI biases than negative ones. Positive LAI errors of 50% resulted in up to 50% changes in ET, while negative biases of 50% in LAI caused less than 10% deviations in ET. However, even when ET changes were minimal, negative LAI errors of 50% led to up to a 40% reduction in modeled transpiration, as soil evaporation and plant transpiration responded to LAI change divergently. These findings call for careful consideration of satellite LAI uncertainties for ET modeling, especially for the partitioning of water loss between vine and soil or cover crop for effective vineyard irrigation management.
We examine the global water cycle characteristics in the Accelerated Climate Modeling for Energy v0.3 model (a close relative to version 5.3 of the Community Atmosphere Model) in atmosphere-only simulations spanning the years 1980–2005. We evaluate the simulations using a broad range of observational and reanalysis datasets, examine how the simulations change when the horizontal resolution is increased from 1° to 0.25, and compare the simulations against models participating in the the Atmosphere Model Intercomparison Project of the 5th Coupled Model Intercomparison Project (CMIP5). Particular effort has been made to evaluate the model using the best available observational estimates and verifying model biases with additional datasets when differences are known to exist among the observations. Regardless of resolution, the model exhibits several biases: global-mean precipitation, evaporation, and precipitable water are too high, light precipitation occurs too frequently, and the atmospheric residence time of water is too short. Many of these biases are shared by the multi-model mean climate of models participating in CMIP5. The reasons behind regional biases in precipitation are discussed by examining how different fields, such as local evaporation and transport of water vapor, contribute to the bias. Although increasing the horizontal resolution does not drastically change the water cycle, it does lead to a few differences: an increase in global mean precipitation rate, an increase in the fraction of total precipitation that falls over land, more frequent heavy precipitation (>30 mm day -1 ), and a decrease in precipitable water. One of the most notable changes is the shift of precipitation produced by the convective parameterization to that produced by the large-scale microphysics parameterization. We analyze how changes in moisture and circulation with resolution contribute to this shift in the precipitation partitioning. Because changing horizontal resolution requires some re-tuning, the effect of that tuning was evaluated by performing an additional simulation at 1 but using the tunings from the 0.25 simulation. In conclusion, the evaluation shows that the more frequent heavy precipitation, the decrease in precipitable water, and the shift from convective to large-scale precipitation are predominantly due to resolution changes, while tuning changes have a major influence on the global mean precipitation and the land/ ocean partitioning of precipitation.
This paper analyzes the limited range, spatial load balancing problem for agents deployed in non-convex environments and subject to differential constraints which restricts how the agents can move. First, the (unlimited range) spatial load balancing problem is introduced and the minimization problem with area constraints is defined. Then, to extend the problem for limited ranges, two cost functions and a sub-partition are defined. The problems are then analyzed and the results prove the existence of a partition that satisfies the area constraints. The non-convex environment makes the problem difficult to solve in continuous-space. Therefore, a probabilistic roadmap is used to approximate agents’ cells via a graph. A distributed algorithm is proven to converge to an approximate solution. Lastly, the convergence of the algorithm is shown in simulation.
Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.
In this paper, we focus on the mechanisms of phase transformations in additively manufactured Ti–6Al–4V during cooling. In particular, the goal is to understand if the imposed thermal cycles during fabrication results in the complete transformation of the α' to the β phase or the sub-transus decomposition of α' (martensite) to α + β. To this effect, samples fabricated using electron beam melting and laser-directed energy deposition techniques were analyzed using atom probe tomography (APT) in conjunction with correlative transmission Kikuchi diffraction (TKD). While the composition measurement using APT shows partitioning of vanadium into the β phase, the crystallographic analysis suggests evidence of a shear-induced transformation. Despite the pronounced differences in the processing conditions, both of the additive manufacturing techniques lead to similar partitioning of vanadium to the β phase. Finally, calculations using THERMOCALC and DICTRA show that under the time and temperature regimes of additive manufacturing the microstructure could develop by the decomposition reaction of α' → α+β.
Abstract We present a class of high-order Eulerian–Lagrangian Runge–Kutta finite volume methods that can numerically solve Burgers’ equation with shock formations, which could be extended to general scalar conservation laws. Eulerian–Lagrangian (EL) and semi-Lagrangian (SL) methods have recently seen increased development and have become a staple for allowing large time-stepping sizes. Yet, maintaining relatively large time-stepping sizes post shock formation remains quite challenging. Our proposed scheme integrates the partial differential equation on a space-time region partitioned by linear approximations to the characteristics determined by the Rankine–Hugoniot jump condition. We trace the characteristics forward in time and present a merging procedure for the mesh cells to handle intersecting characteristics due to shocks. Following this partitioning, we write the equation in a time-differential form and evolve with Runge–Kutta methods in a method-of-lines fashion. High-resolution methods such as ENO and WENO-AO schemes are used for spatial reconstruction. Extension to higher dimensions is done via dimensional splitting. Numerical experiments demonstrate our scheme’s high-order accuracy and ability to sharply capture post-shock solutions with large time-stepping sizes.
Multivariate classification algorithms are a common tool in contemporary data science that have begun to be applied to nuclear forensic analyses. Using a multivariate generalization of quantile–quantile plots for comparing unknown statistical distributions, a new model-free multivariate classifier called the Quantile–Quantile Comparator has been developed and tested on the analysis of simulated irradiated nuclear fuel. A method to estimate the sample-specific probability of having made an incorrect classification decision by analyzing the distribution of quantile comparisons has been developed, and methods have been developed to analyze the partition of the known data library used to analyze unknown data. By analyzing this partition, the analyst may identify classes that are likely to be confused, identify test data that are inconsistent with the data library and return a “None-of-the-Above” classification decision, and optimize the class boundaries. In this paper, the development of these capabilities is described, and a case study using real experimental assay data collected from nuclear fuel extracted from the newly-released In conclusion, Spent Fuel Isotopic Composition Database to demonstrate the efficacy of these capabilities is presented.
In petascale systems with a million CPU cores, scalable and consistent I/O performance is becoming increasingly difficult to sustain mainly because of I/O variability. Furthermore, the I/O variability is caused by concurrently running processes/jobs competing for I/O or a RAID rebuild when a disk drive fails. We present a mechanism that stripes across a selected subset of I/O nodes with the lightest workload at runtime to achieve the highest I/O bandwidth available in the system. In this paper, we propose a probing mechanism to enable application-level dynamic file striping to mitigate I/O variability. We also implement the proposed mechanism in the high-level I/O library that enables memory-to-file data layout transformation and allows transparent file partitioning using subfiling. Subfiling is a technique that partitions data into a set of files of smaller size and manages file access to them, making data to be treated as a single, normal file to users. Here, we demonstrate that our bandwidth probing mechanism can successfully identify temporally slower I/O nodes without noticeable runtime overhead. Experimental results on NERSC’s systems also show that our approach isolates I/O variability effectively on shared systems and improves overall collective I/O performance with less variation.
Abstract The present paper aims to discuss the functional and ecophysiological traits of two abundant succulent halophytes in Mediterranean salt marsh systems, considering two ecotypes differing on their tidal exposure. In Halimione portulacoides the higher root/shoot (R/S) biomass ratio verified in low inundation frequency (LF) marshes, as compared with that in high inundation frequency (HF), indicates an optimal partitioning strategy, inducing differential allocation patterns along with varying environmental factors. Conversely, Sarcocornia perennis appear to have an isometric allocation strategy, based on intrinsic biomass allocation mechanisms independent from the surrounding environmental conditions. Similarly, the photosynthetic traits appear to reflect the intrinsic ecology of the species. Sarcocornia perennis habitat adaptation to HF conditions is clearly revealed by its high photosynthetic efficiency under HF conditions. On the other hand, the cosmopolitan H. portulacoides shows no differences between ecotypes, in which concerns this trait, mostly due to the high carotenoid content of the HF ecotype, which allows this specie to counteract the stress generated during submersion. Additionally, anti‐oxidant enzymatic activities revealed that S. perennis presents a high degree of stress tolerance under HF conditions, while H. portulacoides is highly adapted to LF conditions. These functional (biomass‐related) and physiological traits determine the optimal habitats for H. portulacoides and S. perennis . While H. portulacoides optimal biomass partitioning, along with its efficient anti‐oxidant defence system, makes this species fitter to LF conditions, S. perennis isometric allocation strategy, along with a higher photosynthetic efficiency under frequent flooding conditions, provides this species the mechanisms to efficiently colonize the intertidal habitat.