Given that approximate quantum error-correcting (AQEC) codes have a potentially better performance than perfect quantum error correction codes, it is pertinent to quantify their performance. While quantum weight enume...
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ISBN:
(纸本)9781728164328
Given that approximate quantum error-correcting (AQEC) codes have a potentially better performance than perfect quantum error correction codes, it is pertinent to quantify their performance. While quantum weight enumerators establish some of the best upper bounds on the minimum distance of quantum error-correcting codes, these bounds do not directly apply to AQEC codes. Herein, we introduce quantum weight enumerators for amplitude damping (AD) errors and work within the framework of approximate quantum error correction. In particular, we introduce an auxiliary exact weight enumerator that is intrinsic to a code space and moreover, we establish a linear relationship between the quantum weight enumerators for AD errors and this auxiliary exact weight enumerator. This allows us to establish a linear program that is infeasible only when AQEC AD codes with corresponding parameters do not exist. To illustrate our linear program, we numerically rule out the existence of three-qubit AD codes that are capable of correcting an arbitrary AD error.
作者：
Varghese, CinuSrivastav, Prem PrakashIIT
Ctr Rural Dev & Innovat Sustainable Technol Kharagpur 721302 W Bengal India IIT
Agr & Food Engn Dept Kharagpur 721302 W Bengal India
The present study focuses on the development and sensory characterization of low-cost, high-energy, nutritious cookies that satisfy the 30% Recommended Dietary Allowance (RDA) requirement of undernourished adolescents...
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The present study focuses on the development and sensory characterization of low-cost, high-energy, nutritious cookies that satisfy the 30% Recommended Dietary Allowance (RDA) requirement of undernourished adolescents as per the National Institute of Nutrition (NIN), India. The underutilized ingredients finger millet, jackfruit seed powder, moringa powder, soy protein isolate, icing sugar, and oil were optimized using linear programming (LP). The sensory attributes of the developed cookies were compared with imported BP-100 (RUTF biscuit) and two high-energy biscuits available in the market using Fuzzy logic analysis. Cookies with a total energy of 506.81 kcal/100 g, protein 13.46 g/100 g, and fat 25.97 g/100 g were developed at an ingredient cost of US$ 1.52/kg, with the dose of vitamin and mineral premix set at 2.2 g/100 g of cookies. The developed cookies with higher similarity values showed higher consumer acceptability compared to other samples. The texture and taste have the most effect on sensory acceptability and customer approval, following color, overall acceptability, and flavor. Industrial relevance: In terms of utilizing the locally available ingredients to combat adolescent malnutrition, linear programming, and fuzzy logic are easy methods that can be employed in any World Food Program initiative to formulate low-cost, high-energy food products.
Empirical quantiles for finitely distributed univariate random variables can be obtained by solving a certain linear program. It is shown in this short note that multivariate empirical quantiles can be obtained in a v...
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An algorithm that solves a linear program with planes exterior to the feasible region is described. Given a linear program in a standard form, a constraint derived from the objective function is added to make the prog...
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Laboratory automation and mathematical optimization are key to improving the efficiency of synthetic biology research. While there are algorithms optimizing the construct designs and synthesis strategies for DNA assem...
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Laboratory automation and mathematical optimization are key to improving the efficiency of synthetic biology research. While there are algorithms optimizing the construct designs and synthesis strategies for DNA assembly, the optimization of how DNA assembly reaction mixes are prepared remains largely unexplored. Here, we focus on reducing the pipette tip consumption of a liquid-handling robot as it delivers DNA parts across a multi-well plate where several constructs are being assembled in parallel. We propose a linear programming formulation of this problem based on the capacitated vehicle routing problem, as well as an algorithm which applies a linear programming solver to our formulation, hence providing a strategy to prepare a given set of DNA assembly mixes using fewer pipette tips. The algorithm performed well in randomly generated and real-life scenarios concerning several modular DNA assembly standards, proving to be capable of reducing the pipette tip consumption by up to 59% in large-scale cases. Combining automatic process optimization and robotic liquid handling, our strategy promises to greatly improve the efficiency of DNA assembly, either used alone or combined with other algorithmic DNA assembly optimization methods.
Optimal coordination and settings of directional overcurrent relays (DOCRs) are crucial task to ensure reliable and effective protection in power system networks. The settings of DOCRs are plug setting current (PSC) a...
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Optimal coordination and settings of directional overcurrent relays (DOCRs) are crucial task to ensure reliable and effective protection in power system networks. The settings of DOCRs are plug setting current (PSC) and time multiplier setting (TMS). The DOCRs coordination is well-known as a highly constrained nonlinear optimization problem. Its complexity in terms of non-linearity increases along with the network size increment. This paper proposes a hybrid optimization algorithm which consists of Firefly Algorithm and linear programming (FA-LP) to relax the search space by linearizing the equation of the DOCRs coordination to attain an optimal solution. Furthermore, this paper also considers a mixed type of IEC relay characteristics to attain effective relay operation. The proposed method is tested on the IEEE 8-, 15- and 30-bus test systems. The results show the reduction of total relay operating time between 15.6% and 85.5% as compared to other techniques in the literature and also being verified using the ETAP software.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-ncnd/4.0/).
In this paper, an efficient as well as reliable approach to deal with heat exchanger networks (HENs) synthesis problems, which is inherently known as a mixed-integer non-linear programming model, is presented. The str...
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In this paper, an efficient as well as reliable approach to deal with heat exchanger networks (HENs) synthesis problems, which is inherently known as a mixed-integer non-linear programming model, is presented. The structural variables as the discrete variables are optimized by a genetic algorithm (GA), whereas continuous variables are handled by a modified quasi-linear programming (MQLP) model. Each HEN is considered as a chromosome consisting of a sequence of genes. Each gene also contains the address of the exchanger(s) in the network. The HENs generated by the GA are sent to the MQLP to calculate their overall objective function (OOF) (i.e. minimum total annual cost (TAC)). The MQLP model includes two inner and outer surfaces. On the outer surface, the local optimal values of the continuous variables are found according to the maximum energy recovery of HEN, while on the inner surface, the globally optimal values of them are found to reach the minimum TAC of HEN. Due to the relatively linear behavior of the proposed method, a comparison of results with references showed that this method can reduce TAC of HENs compared to the studied references by about (0.51% to 2.37%). (c) 2021 Elsevier Ltd. All rights reserved.
In this paper, we develop a computationally-efficient approach to minimum-time trajectory optimization using input-output data-based models, to produce an end-to-end data-to-control solution to time-optimal planning/c...
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Load shedding is currently implemented in two ways. In the first, manual load shedding is performed, where transmission system operators, using estimates, inform distribution utilities of predicted stressful condition...
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Load shedding is currently implemented in two ways. In the first, manual load shedding is performed, where transmission system operators, using estimates, inform distribution utilities of predicted stressful conditions and request dispatch of reserves and then emergency load shedding. In the second manner, automatic load shedding is triggered by protection relays as part of under-voltage and under-frequency load shedding schemes. Pre-defined values of load to be shed and the corresponding number of stages are implemented as relay settings. Under-frequency protection relays use only local measurements for decision making. Decision making is done in milliseconds plus breaker time. However, in the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions, traditional under-frequency load shedding schemes can generate sub-optimal solutions during events leading to islanding of the transmission grid. Although phasor measurement units provide a source of information which can be useful for this problem, centralized solutions for automatic load shedding require total processing times which are not acceptable for real-life implementation. In this work, a bi-level linear programming model is presented. The model is implemented in a distributed architecture leveraging phasor measurement unit data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model which leverages predictive estimates of load shedding alternatives to determine the location and load value to be shed. The proposed solution is easy-to-implement and demonstrates high potential for real-world applications.
This paper presents a linear-programming based algorithm to perform data-driven stabilizing control of linear positive systems. A set of state-input-transition observations is collected up to magnitude-bounded noise. ...
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