i-manager's Journal on Mathematics (JMAT)


Volume 13 Issue 1 January - June 2024

Research Paper

Estimation of Quantum Entropies

Alexei Kaltchenko*
Wilfrid Laurier University, Waterloo, Ontario, Canada.
Kaltchenko, A. (2024). Estimation of Quantum Entropies. i-manager’s Journal on Mathematics, 13(1), 1-10. https://doi.org/10.26634/jmat.13.1.20387

Abstract

Motivated by the importance of entropy functions in quantum data compression, entanglement theory, and various quantum information-processing tasks, this study demonstrates how classical algorithms for entropy estimation can effectively contribute to the construction of quantum algorithms for universal quantum entropy estimation. Given two quantum i.i.d. sources with completely unknown density matrices, algorithms are developed for estimating quantum cross entropy and quantum relative entropy. These estimation techniques represent a quantum generalization of the classical algorithms by Lempel, Ziv, and Merhav.

Research Paper

Global Stability of a Predator-Prey Fishery Model with Non-Selective Harvesting: A Study of Linear Optimal Control

Cephas Tay-Suka*
Department of Mathematics, University of Cape Coast, Cape Coast, Ghana.
Tay-Suka, C. (2024). Global Stability of a Predator-Prey Fishery Model with Non-Selective Harvesting: A Study of Linear Optimal Control. i-manager’s Journal on Mathematics, 13(1), 11-26. https://doi.org/10.26634/jmat.13.1.20916

Abstract

A proposed two-dimensional modified Lotka-Volterra fishery model in terms of predator-prey aims to explore the effect of non-selective harvesting on the predator and prey populations. The study delves into various essential aspects of the dynamical system, including positivity, uniform boundedness, and persistence. Points of equilibrium are identified. The system's local and global stability are thoroughly examined and discussed. Moreover, the research explores the concept of bionomic equilibrium, a scenario where economic rent is entirely dissipated. Extending the bioeconomic model, the study investigates a linear optimal control problem to determine the most effective harvesting strategy. Utilising Pontryagin's maximum principle, the optimal control is characterised. The findings indicate that maximum allowable effort should be exerted whenever the net revenue per unit effort surpasses the total net marginal revenue of predator and prey stocks. Numerical simulations, using data on the marine artisanal fishery in Ghana, are conducted to validate the theoretical discoveries. The outcomes reveal that the fishery can support sustainable harvesting of both predator (tuna) and prey (sardinella) populations, as long as the optimal harvesting effort is set at 100,000 fishing trips annually.

Research Paper

Comparative Analysis of Finite Difference Method (FDM) and Physics-Informed Neural Networks (PINNs)

Wasif Khan* , Shahbaz Ahmad**
*-**Department of Mathematics, Government College University, Lahore, Pakistan.
Khan, W., and Ahmad, S. (2024). Comparative Analysis of Finite Difference Method (FDM) and Physics-Informed Neural Networks (PINNs). i-manager’s Journal on Mathematics, 13(1), 27-37. https://doi.org/10.26634/jmat.13.1.20383

Abstract

In this analysis, the solutions of the Linear and Non-Linear models are explored and compared using two distinct methods: the Finite Difference Method (FDM) and the Physics-Informed Neural Networks (PINNs). Initially, the solution is derived employing the principles of FDM, followed by solving the same problem using the methodology of PINNs. Subsequently, a comparative examination of the solution graphs with the exact solution is conducted.

Research Paper

The Hull Domination Number of a Graph

V. Mary Gleeta* , C. N. Celine Priya **
*-** Department of Mathematics, Tirunelveli Dakshina Mara Nadar Sangam College (TDMNS), Kallikulam, Tirunelveli, India.
Gleeta, V. M., and Priya, C. N. C. (2024). The Hull Domination Number of a Graph. i-manager’s Journal on Mathematics, 13(1), 38-45. https://doi.org/10.26634/jmat.13.1.20570

Abstract

For a connected graph G = (V, E), the hull number h(G) of a graph G is the minimum cardinality of a set of vertices whose convex hull contains all vertices of G. A hull set S in a connected graph G is called a minimal hull set of G if no proper subset of S is a hull set of G.A subset D of vertices in G is called a dominating set if every vertex not in D has at least one neighbor in D. A Hull dominating set M is both a Hull and a dominating set. The hull (domination, hull domination) number h(G),(γ(G),γh (G)) of G is the minimum cardinality among all hull (dominating, hull dominating) sets in G. Hull domination number of certain classes of graphs are determined. Connected graph of order p with hull domination number p or p-1 are characterized. It is shown that for every two integers a,b≥2 with 2≤a≤b, there is a connected graph G such that γh (G)=a and γg (G)=b, where γg (G) is the geodetic domination number of a graph.

Research Paper

K Out of N Integrated Reliability Model with Multiple Stage Optimization using Four Components of Heuristic Programming Approach

Srinivasa Rao Velampudi* , M. Krishna**
*-** Department of Mathematics, Raghu Engineering College, Visakhapatnam, Andhra Pradesh, India.
Velampudi, S. R., and Krishna, M. (2024). K Out of N Integrated Reliability Model with Multiple Stage Optimization using Four Components of Heuristic Programming Approach. i-manager’s Journal on Mathematics, 13(1), 46-55. https://doi.org/10.26634/jmat.13.1.20189

Abstract

Integer variables are among the neo-logistic programming issues that most frequently pertain to system reliability improvement. If 'k' out of 'n' elements are present in each technology, then the configuration can be employed with 'k' out of 'n' systems. Only particular objective function structures and restrictions may be used in a heuristic technique to precisely address a dependability optimization problem. As more constraints are placed on it, the more useful it becomes; it is worthless for boosting dependability in a large system. This paper analyzes existing research on integrated reliability models with redundancy and explores system reliability optimization before proposing new recommendations.