New Methods for Characterizing Phases of 2D Supersymmetric Gauge Theories

We study the physics of two-dimensional N=(2,2) gauged linear sigma models (GLSMs) via the two-sphere partition function. We show that the classical phase boundaries separating distinct GLSM phases, which are described by the secondary fan construction for abelian GLSMs, are completely encoded in the analytic structure of the partition function. The partition function of a non-abelian GLSM can be obtained as a limit from an abelian theory; we utilize this fact to show that the phases of non-abelian GLSMs can be obtained from the secondary fan of the associated abelian GLSM. We prove that the partition function of any abelian GLSM satisfies a set of linear differential equations; these reduce to the familiar A-hypergeometric system of Gel'fand, Kapranov, and Zelevinski for GLSMs describing complete intersections in toric varieties. We develop a set of conditions that are necessary for a GLSM phase to admit an interpretation as the low-energy limit of a non-linear sigma model with a Calabi-Yau threefold target space. Through the application of these criteria we discover a class of GLSMs with novel geometric phases corresponding to Calabi-Yau manifolds that are branched double-covers of Fano threefolds. These criteria provide a promising approach for constructing new Calabi-Yau geometries.Comment: 25 pages + references, appendices. v2: references added, typos corrected. v3: two small typos correcte

Learning scalable and transferable multi-robot/machine sequential assignment planning via graph embedding

Can the success of reinforcement learning methods for simple combinatorial optimization problems be extended to multi-robot sequential assignment planning? In addition to the challenge of achieving near-optimal performance in large problems, transferability to an unseen number of robots and tasks is another key challenge for real-world applications. In this paper, we suggest a method that achieves the first success in both challenges for robot/machine scheduling problems. Our method comprises of three components. First, we show a robot scheduling problem can be expressed as a random probabilistic graphical model (PGM). We develop a mean-field inference method for random PGM and use it for Q-function inference. Second, we show that transferability can be achieved by carefully designing two-step sequential encoding of problem state. Third, we resolve the computational scalability issue of fitted Q-iteration by suggesting a heuristic auction-based Q-iteration fitting method enabled by transferability we achieved. We apply our method to discrete-time, discrete space problems (Multi-Robot Reward Collection (MRRC)) and scalably achieve 97% optimality with transferability. This optimality is maintained under stochastic contexts. By extending our method to continuous time, continuous space formulation, we claim to be the first learning-based method with scalable performance among multi-machine scheduling problems; our method scalability achieves comparable performance to popular metaheuristics in Identical parallel machine scheduling (IPMS) problems

Importance of understanding variable and transient energy demand in large multi-product industrial plants for process integration

There have been some news releases claiming that Professor Henle in Germany has found the chemical identity of UMF, and that in future chemical analysis will be used instead of assays of antibacterial activity to indicate the level of UMF in manuka honey. Both of these claims are misleading. Because the level of active substance in manuka honey is an unreliable indication of the level of antibacterial activity and can be very misleading, it is hard to see any commercial advantage for it to be used to indicate antibacterial activity other than if someone wanted to fool the consumer into thinking that the higher numbers are giving them a level of antibacterial activity that is far higher than they are really getting

The Landscape of M-theory Compactifications on Seven-Manifolds with G2G_2 Holonomy

We study the physics of globally consistent four-dimensional $\mathcal{N}=1$ supersymmetric M-theory compactifications on $G_2$ manifolds constructed via twisted connected sum; there are now perhaps fifty million examples of these manifolds. We study a rich example that exhibits $U(1)^3$ gauge symmetry and a spectrum of massive charged particles that includes a trifundamental. Applying recent mathematical results to this example, we compute membrane instanton corrections to the superpotential and spacetime topology change in a compact model; the latter include both the (non-isolated) $G_2$ flop and conifold transitions. The conifold transition spontaneously breaks the gauge symmetry to $U(1)^2$, and associated field theoretic computations of particle charges make correct predictions for the topology of the deformed $G_2$ manifold. We discuss physical aspects of the abelian $G_2$ landscape broadly, including aspects of Higgs and Coulomb branches, membrane instanton corrections, and some general aspects of topology change.Comment: v1: 37 pages. v2: references added. v3: more discussion of instanton zero modes. JHEP version v4: references correcte

Potential repellency of cedarwood oil from a novel extraction method to stored product insects

Producers lose 10-30% of crops during storage, processing, and marketing after harvest each year to stored product insects (1,2). Globally, there has been a rise in insecticide resistance to phosphine, the most common fumigant for these pests (3). As a result, producers need to diversify post-harvest IPM methods to preserve existing tools. One alternative strategy is push-pull, whereby a repellent is used to “push” an insect away from the commodity of interest, while also simultaneously “pulling” the insects to an alternate location away from the commodity using an attractant (4)(Fig. 1). This system notably requires a long-distance repellent. One potential repellent includes cedarwood oil, which has shown repellency to termites and ants (5,6). A novel extraction process for this compound has been developed, which leaves many of its main constituents intact (7). However, to date, this compound has never been assessed for repellency to post-harvest insects

Accuracy of 2 telemetry systems in mountainous terrain

Spring 1992.Summary report 1988-1991.Conducted for: Colorado Division of Wildlife, Vail Associates, Arrohead and Vail, The Rocky Mountain Elk Foundation, U.S. Forest Service.Includes bibliographical references

Game Theory Analysis of Aircraft Manufacturer Innovation Strategies in the Face of Increasing Airline Fuel Costs

The air transportation system is a vital infrastructure that enables economic growth and provides significant social benefits. Future increases and volatility in crude oil prices, as well as environmental charges, are likely to increase the effective cost of fuel. We investigate the impacts of effective fuel cost increase on the US air transportation system historically and perform a game theory analysis of the impact of manufacturer competition on the introduction of new, more fuel efficient aircraft. The cost of jet fuel increased 244% between July 2004 and July 2008, providing a natural experiment to evaluate how fuel price increase affected continental US networks and fleets. It was found that non-hub airports serving small communities lost 12% of connections, compared to a system-wide average loss of 2.8%. Increased effective fuel costs will provide incentives for airlines to improve fleet fuel efficiency, reducing the environmental impacts of aviation, but may cause an uneven distribution of social and economic impacts if small communities suffer greater loss of mobility. Government action may be required to determine acceptable levels of access as the system transitions to higher fuel costs. Technology innovation may act as a long-term hedge against increasing effective fuel costs, enabling mobility to be maintained. The single aisle commercial aircraft market segment is the largest, but has the longest running product lines. We hypothesize that competition has important effects on manufacturers’ decisions to innovate that must be considered when designing policies to reduce fleet emissions. An aircraft program valuation model is developed to estimate expected payoffs to manufacturers under competitive scenarios. A game theory analysis demonstrates how the incentives to innovate may be altered by subsidies, technology forcing regulations, increased effective fuel costs, the threat of new entrants, and long-term competitive strategies. Increased competition may result in incumbent manufacturers producing re-engined aircraft while increased effective fuel costs may result in new aircraft programs. Incumbents’ optimal strategies may be to delay the entry of new single aisle aircraft until 2020-24, unless technology forcing regulations are implemented.This work was supported by the MIT/Masdar Institute of Science and Technology under grant number Mubadala Development Co. Agreement 12/1/06. The authors wish to thank PARTNER for access to the Piano-X software package and Robert M. Peterson from the Boeing Corporation for his valuable feedback on the aircraft program valuation model. Any errors are the authors’ alone

Non-continuous and variable rate processes: Optimisation for energy use

The need to develop new and improved ways of reducing energy use and increasing energy intensity in industrial processes is currently a major issue in New Zealand. Little attention has been given to optimisation of non-continuous processes in the past, due to their complexity, yet they remain an essential and often energy intensive component of many industrial sites. Novel models based on pinch analysis that aid in minimising utility usage have been constructed here through the adaptation of proven continuous techniques. The knowledge has been integrated into a user friendly software package, and allows the optimisation of processes under variable operating rates and batch conditions. An example problem demonstrates the improvements in energy use that can be gained when using these techniques to analyse non-continuous data. A comparison with results achieved using a pseudo-continuous method show that the method described can provide simultaneous reductions in capital and operating costs

A derivative method for minimising total cost in heat exchanger networks through optimal area allocation

This paper presents a novel Cost Derivative Method (CDM) for finding the optimal area allocation for a defined Heat Exchanger Network (HEN) structure and stream data, without any stream splits to achieve minimum total cost. Using the Pinch Design Method (PDM) to determine the HEN structure, the approach attempts to add, remove and shift area to exchangers where economic benefits are returned. From the derivation of the method, it is found that the slope of the ε-NTU relationship for the specific heat exchanger type, in combination with the difference in exchanger inlet temperatures and the overall heat transfer coefficient, are critical to calculating the extra overall duty each incremental area element returns. The approach is able to account for differences in film coefficients, heat exchanger types, flow arrangements, exchanger cost functions, and utility pricing. Incorporated into the method is the newly defined “utility cost savings flow-on” factor, θ, which evaluates downstream effects on utility use and cost that are caused by changing the area of one exchanger. To illustrate the method, the CDM is applied to the distillation example of Gundersen (2000). After applying the new CDM, the total annual cost was reduced by 7.1 % mainly due to 24 % less HEN area for similar heat recovery. Area reduction resulted from one exchanger having a minimum approach temperature (ΔTmin) of 7.7 °C while the other recovery exchangers had larger ΔTmin values. The optimum ΔTmin for the PDM was 12.5 °C. The CDM solution was found to give a comparable minimum total area and cost to two recently published programming HEN synthesis solutions for the same problem without requiring the increased network complexity through multiple stream splits