Jump to content

Trigintaduonion

From Wikipedia, the free encyclopedia
Trigintaduonions
Symbol
TypeHypercomplex algebra
Unitse0, ..., e31
Multiplicative identitye0
Common systems
Less common systems

In abstract algebra, the trigintaduonions, also known as the 32-ions, 32-nions, or sometimes pathions (),[1][2][3] form a 32-dimensional algebra over the real numbers,[4] usually represented by the capital letter T, boldface T or blackboard bold .[5]

The trigintaduonions are obtained by applying the Cayley–Dickson construction to the sedenions. Applying the Cayley–Dickson construction to the sedenions yields a 64-dimensional algebra called the 64-ions or sexagintaquattuornions, sometimes also known as the chingons.[6][7][8]

Multiplication

[edit]

Whereas octonion unit multiplication can be visually represented by PG(2,2) (also known as the Fano plane) and sedenion unit multiplication by PG(3,2), trigintaduonion unit multiplication can be visually represented by PG(4,2).[9]

The multiplication of the unit trigintaduonions is illustrated in the two tables below.[10]

Below is the trigintaduonion multiplication table for 0 to 15. The top half of this table corresponds to the multiplication table for the sedenions.

Below is the trigintaduonion multiplication table for 16 to 31.

The first computational algorithm for the multiplication of trigintaduonions was developed by Cariow & Cariowa in 2014.[11]

Applications

[edit]

The trigintaduonions have applications in particle physics,[12] quantum mechanics, and other branches of modern physics.[10] More recently, the trigintaduonions and other hypercomplex numbers have also been used in neural network research.[13]

References

[edit]
  1. ^ de Marrais, Robert P. C. (2002). "Flying Higher Than a Box-Kite: Kite-Chain Middens, Sand Mandalas, and Zero-Divisor Patterns in the 2n-ions Beyond the Sedenions". arXiv:math/0207003. doi:10.48550/arXiv.math/0207003.
  2. ^ "Trigintaduonion". University of Waterloo. Retrieved 2024-10-08.
  3. ^ Cawagas, Raoul E.; Carrascal, Alexander S.; Bautista, Lincoln A.; Maria, John P. Sta.; Urrutia, Jackie D.; Nobles, Bernadeth (2009). "The Subalgebra Structure of the Cayley-Dickson Algebra of Dimension 32 (trigintaduonion)". arXiv:0907.2047v3. doi:10.48550/arXiv.0907.2047.
  4. ^ Saini, Kavita; Raj, Kuldip (2021). "On generalization for Tribonacci Trigintaduonions". Indian Journal of Pure and Applied Mathematics. 52 (2). Springer Science and Business Media LLC: 420–428. doi:10.1007/s13226-021-00067-y. ISSN 0019-5588.
  5. ^ Cawagas, Raoul E.; Carrascal, Alexander S.; Bautista, Lincoln A.; Maria, John P. Sta.; Urrutia, Jackie D.; Nobles, Bernadeth (2009-07-12). "The Subalgebra Structure of the Cayley-Dickson Algebra of Dimension 32 (trigintaduonion)". arXiv:0907.2047. Retrieved 2024-10-10.
  6. ^ Carter, Michael (2011-08-19). "Visualization of the Cayley-Dickson Hypercomplex Numbers Up to the Chingons (64D)". MaplePrimes. Retrieved 2024-10-08.
  7. ^ "Application Center". Maplesoft. 2010-01-18. Retrieved 2024-10-08.
  8. ^ Valkova-Jarvis, Zlatka; Poulkov, Vladimir; Stoynov, Viktor; Mihaylova, Dimitriya; Iliev, Georgi (2022-03-18). "A Method for the Design of Bicomplex Orthogonal DSP Algorithms for Applications in Intelligent Radio Access Networks". Symmetry. 14 (3). MDPI AG: 613. doi:10.3390/sym14030613. ISSN 2073-8994.
  9. ^ Saniga, Metod; Holweck, Frédéric; Pracna, Petr (2015-12-04). "From Cayley-Dickson Algebras to Combinatorial Grassmannians". Mathematics. 3 (4). MDPI AG: 1192–1221. arXiv:1405.6888. doi:10.3390/math3041192. ISSN 2227-7390.
  10. ^ a b Weng, Zi-Hua (2024-07-23). "Gauge fields and four interactions in the trigintaduonion spaces". Mathematical Methods in the Applied Sciences. Wiley. doi:10.1002/mma.10345. ISSN 0170-4214.
  11. ^ Cariow, A.; Cariowa, G. (2014). "An algorithm for multiplication of trigintaduonions". Journal of Theoretical and Applied Computer Science. 8 (1): 50–75. ISSN 2299-2634. Retrieved 2024-10-10.
  12. ^ Weng, Zihua (2007-04-02). "Compounding Fields and Their Quantum Equations in the Trigintaduonion Space". arXiv:0704.0136. Retrieved 2024-10-10.
  13. ^ Baluni, Sapna; Yadav, Vijay K.; Das, Subir (2024). "Lagrange stability criteria for hypercomplex neural networks with time varying delays". Communications in Nonlinear Science and Numerical Simulation. 131. Elsevier BV: 107765. doi:10.1016/j.cnsns.2023.107765. ISSN 1007-5704.