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Articles 1 - 18 of 18
Full-Text Articles in Algebra
Learning With Errors Parameter Analysis, Archana Parameswaran
Learning With Errors Parameter Analysis, Archana Parameswaran
Cybersecurity Undergraduate Research Showcase
We implement a systematic approach for generating, evaluating, and benchmarking Learning with Errors implementations in Sage Math by varying lattice dimensions, moduli, error standard deviations, and multiple error distributions to observe concrete security-efficiency tradeoffs. The security estimator maps parameter sets to concrete security levels and bits, while performance metrics measured computational efficiency and memory requirements. Results indicate that various distribution types do not significantly impact security, though binomial distributions require more computational overhead than discrete gaussian or uniform. Memory requirements increased when modulus q increased from 12289 to 65537. Larger dimensions have an exponentially growing requirement for memory, but this …
Multipliers On Weighted Sequence Spaces, Gilbert Acheampong, Raymond Cheng
Multipliers On Weighted Sequence Spaces, Gilbert Acheampong, Raymond Cheng
Mathematics & Statistics Faculty Publications
The space ℓp,α of complex sequences a = (a0, a1,a2,...) for which
[[formula omitted]]
is studied. Each such sequence can be identified with the analytic function with power series
[[formula omitted]]
In this setting, the point evaluation and the difference quotient mappings are shown to be bounded; the cases are identified in which ℓp,α is boundedly contained in ℓr,β. Conditions on the parameters are derived for the analytic functions of ℓp,α to have radial limits almost everywhere on the boundary, and for ℓp,α to be an algebra. Smoothness properties of the boundary function are investigated. Basic properties of multipliers on …
Multipliers Between ℓᴾ Spaces, Raymond Cheng
Multipliers Between ℓᴾ Spaces, Raymond Cheng
Mathematics & Statistics Faculty Publications
For 0 < p ⩽ ∞ and 0 < r ⩽ ∞, the space 𝔐p,r of (coefficient) multipliers from ℓp and ℓr is completely characterized. This is elementary in most instances. The interesting case 0 < r < p < ∞ requires more effort, and it is shown that a sequence of complex numbers belongs to 𝔐p,r if and only if the sequence of their absolute values has a non increasing rearrangement (h0,h1,h2,...) satisfying
(∞
Σ (k +1)(p-r)/p (hrk - hrk+1)1/r) < ∞
k = 0
In that case, the expression on the left is the norm of the multiplier, and it is a compact operator. Further upper and lower bounds are given for the multiplier norm.
Generalized Functions In The Study Of Signals And Systems, Erik I. Verriest, Gunther Dirr, W. Steven Gray
Generalized Functions In The Study Of Signals And Systems, Erik I. Verriest, Gunther Dirr, W. Steven Gray
Electrical & Computer Engineering Faculty Publications
We collect three instances where the theory of generalized functions may still make contributions to the study of signals and systems. In the first, a purely algebraic approach is presented for LTI-ODE's, in terms of two operators, D and T, respectively the differentiation operator and the multiplication-by-the-independent-variable operator. This formalism adds simplicity, a duality theory, and nicely generalizes to other classes of operator equations and their solutions. In the second part we extend the classical bilateral Laplace transform to include Bohl functions with support in ℝ by invoking Sato's hyperfunctions. Finally, in the third case we use the Colombeau algebra …
The Vulnerabilities To The Rsa Algorithm And Future Alternative Algorithms To Improve Security, James Johnson
The Vulnerabilities To The Rsa Algorithm And Future Alternative Algorithms To Improve Security, James Johnson
Cybersecurity Undergraduate Research Showcase
The RSA encryption algorithm has secured many large systems, including bank systems, data encryption in emails, several online transactions, etc. Benefiting from the use of asymmetric cryptography and properties of number theory, RSA was widely regarded as one of most difficult algorithms to decrypt without a key, especially since by brute force, breaking the algorithm would take thousands of years. However, in recent times, research has shown that RSA is getting closer to being efficiently decrypted classically, using algebraic methods, (fully cracked through limited bits) in which elliptic-curve cryptography has been thought of as the alternative that is stronger than …
Algebraic Tunnelling, Gaurab Sedhain
Algebraic Tunnelling, Gaurab Sedhain
2023 REYES Proceedings
We study the quantum phenomenon of tunnelling in the framework of algebraic quantum theory, motivated by the tunnelling aspects of false vacuum decay. We see that resolvent C*-algebra, proposed relatively recently by Buchholz and Grundling rather than Weyl algebra provides an appropriate framework for treating the dynamics of non-free quantum mechanical system as an algebraic automorphism. At the end, we propose to investigate false vacuum decay in algebraic quantum field theoretic setting in terms of the two-point correlation function which gives us the tunneling probability, with the corresponding C*-algebraic construction.
On The Geometry Of The Multiplier Space Of ℓPA, Christopher Felder, Raymond Cheng
On The Geometry Of The Multiplier Space Of ℓPA, Christopher Felder, Raymond Cheng
Mathematics & Statistics Faculty Publications
For p ∊ (1, ∞)\ {2}, some properties of the space Mp of multipliers on ℓpA are derived. In particular, the failure of the weak parallelogram laws and the Pythagorean inequalities is demonstrated for Mp. It is also shown that extremal multipliers on the ℓpA spaces are exactly the monomials, in stark contrast to the p = 2 case.
Formal Power Series Approach To Nonlinear Systems With Static Output Feedback, G.S. Venkatesh, W. Steven Gray
Formal Power Series Approach To Nonlinear Systems With Static Output Feedback, G.S. Venkatesh, W. Steven Gray
Electrical & Computer Engineering Faculty Publications
The goal of this paper is to compute the generating series of a closed-loop system when the plant is described in terms of a Chen-Fliess series and static output feedback is applied. The first step is to reconsider the so called Wiener-Fliess connection consisting of a Chen-Fliess series followed by a memoryless function. Of particular importance will be the contractive nature of this map, which is needed to show that the closed-loop system has a Chen-Fliess series representation. To explicitly compute the generating series, two Hopf algebras are needed, the existing output feedback Hopf algebra used to describe dynamic output …
Dimensional Analysis: Physical Insight Gained Through Algebra, John A. Adam
Dimensional Analysis: Physical Insight Gained Through Algebra, John A. Adam
Mathematics & Statistics Faculty Publications
No abstract provided.
Fast Multipole Method Using Cartesian Tensor In Beam Dynamic Simulation, He Zhang, He Huang, Rui Li, Jie Chen, Li-Shi Luo
Fast Multipole Method Using Cartesian Tensor In Beam Dynamic Simulation, He Zhang, He Huang, Rui Li, Jie Chen, Li-Shi Luo
Mathematics & Statistics Faculty Publications
The fast multipole method (FMM) using traceless totally symmetric Cartesian tensor to calculate the Coulomb interaction between charged particles will be presented. The Cartesian tensor based FMM can be generalized to treat other non-oscillating interactions with the help of the differential algebra or the truncated power series algebra. Issues on implementation of the FMM in beam dynamic simulations are also discussed. © 2017 Author(s).
Siso Output Affine Feedback Transformation Group And Its Faá Di Bruno Hopf Algebra, W. Steven Gray, Kurusch Ebrahimi-Fard
Siso Output Affine Feedback Transformation Group And Its Faá Di Bruno Hopf Algebra, W. Steven Gray, Kurusch Ebrahimi-Fard
Electrical & Computer Engineering Faculty Publications
The general goal of this paper is to identify a transformation group that can be used to describe a class of feedback interconnections involving subsystems which are modeled solely in terms of Chen-Fliess functional expansions or Fliess operators and are independent of the existence of any state space models. This interconnection, called an output affine feedback connection, is distinguished from conventional output feedback by the presence of a multiplier in an outer loop. Once this transformation group is established, three basic questions are addressed. How can this transformation group be used to provide an explicit Fliess operator representation of …
Epistemic Strategies For Solving Two-Dimensional Physics Problems, Mary Elyse Hing-Hickman
Epistemic Strategies For Solving Two-Dimensional Physics Problems, Mary Elyse Hing-Hickman
Physics Theses & Dissertations
An epistemic strategy is one in which a person takes a piece of knowledge and uses it to create new knowledge. Students in algebra and calculus based physics courses use epistemic strategies to solve physics problems. It is important to map how students use these epistemic strategies to solve physics problems in order to provide insight into the problem solving process.
In this thesis three questions were addressed: (1) What epistemic strategies do students use when solving two-dimensional physics problems that require vector algebra? (2) Do vector preconceptions in kinematics and Newtonian mechanics hinder a student's ability to apply the …
Vector Operations In Superscalar Architectures, Nathan Daniel Flinn
Vector Operations In Superscalar Architectures, Nathan Daniel Flinn
Electrical & Computer Engineering Theses & Dissertations
Vector calculations are very prevalent today. Though the vector-processing computer is quite an old concept, superscalar processors lack hardware support for vector operations. This thesis investigates whether an ordinary superscalar computer architecture can be designed to include hardware support for improved vector operations without drastically changing the existing superscalar design and behavior. A computer architecture design was created and implemented that included the vector multiply (dot product) operation. The design includes a Vector Operations Unit that captures incoming vector operations and generates the necessary set of machine instructions to complete the vector operation internally. It then delivers these instructions to …
An Invariance Property Of Common Statistical Tests, N. Rao Chaganty, A. K. Vaish
An Invariance Property Of Common Statistical Tests, N. Rao Chaganty, A. K. Vaish
Mathematics & Statistics Faculty Publications
Let A be a symmetric matrix and B be a nonnegative definite (nnd) matrix. We obtain a characterization of the class of nnd solutions Σ for the matrix equation AΣA = B. We then use the characterization to obtain all possible covariance structures under which the distributions of many common test statistics remain invariant, that is, the distributions remain the same except for a scale factor. Applications include a complete characterization of covariance structures such that the chisquaredness and independence of quadratic forms in ANOVA problems is preserved. The basic matrix theoretic theorem itself is useful in other characterizing …
The Sharp Lipschitz-Constants For Feasible And Optimal-Solutions Of A Perturbed Linear Program, Wu Li
The Sharp Lipschitz-Constants For Feasible And Optimal-Solutions Of A Perturbed Linear Program, Wu Li
Mathematics & Statistics Faculty Publications
The purpose of this paper is to derive the sharp Lipschitz constants for the feasible solutions and optimal solutions of a linear program with respect to right-hand-side perturbations. The Lipschitz constants are given in terms of pseudoinverses of submatrices of the matrices involved and are proven to be sharp.
An Artificial Neural Approach To The Decomposition Problem, Chandrashekar L. Masti
An Artificial Neural Approach To The Decomposition Problem, Chandrashekar L. Masti
Electrical & Computer Engineering Theses & Dissertations
The goal of this thesis is to develop an artificial neural approach toward addressing the intractability involved with the decomposition problem. The search for the lattice of substitution property (s. p.) partitions essential to decompositions is cast into the framework of constraint satisfaction. An artificial neural network is developed to provide solutions by performing optimization of a mathematically derived objective function over the problem space. The issue of transitivity is verified to belong to a class of problems beyond the scope of solvability for conventional quadratic-order constraint satisfaction neural networks. A theorem is stated and proved establishing that third-order correlations …
A Note On The Degree Of Approximation With An Optimal, Discrete Polynomial, J. J. Swetits, B. Wood
A Note On The Degree Of Approximation With An Optimal, Discrete Polynomial, J. J. Swetits, B. Wood
Mathematics & Statistics Faculty Publications
A saturation theorem and an asymptotic theorem are proved for an optimal, discrete, positive algebraic polynomial operator. The operator is based on the Gauss-Legendre quadrature formula.
Approximation By Discrete Operators, J. J. Swetits, B. Wood
Approximation By Discrete Operators, J. J. Swetits, B. Wood
Mathematics & Statistics Faculty Publications
A discrete, positive, weighted algebraic polynomial operator which is based on Gaussian quadrature is constructed. The operator is shown to satisfy the Jackson estimate and an optimal version is obtained.