Deep Learning by a Unitary Tensor Network Algorithm Provides Hyperfast Financial Literacy

39 Pages Posted: 6 Feb 2020 Last revised: 24 Jun 2023

See all articles by Alfredo Lacayo Evertsz

Alfredo Lacayo Evertsz

Florida International University - College of Business; Qbit Solutions Research Team

Lizelia Bravo Boza

Qbit Solutions Research Team

Date Written: January 12, 2020

Abstract

We show how tensor network theory (Orús, 2014) and deep learning can be combined to provide a neural tensor network of financial information for hyperfast financial literacy. The resulting minimal-complexity, 5-layered structure encodes an infinite number of probable outcomes into a graphical alphabet made up by 12 superpositioned binary units called double-entries (see fig 1). Using the proposed financial wave function (Schrödinger, 1935), as a computational resource (Biamonte, 2016), we obtain hyperfast processing of financial statements, one pixel at a time. This reveals a highly entangled architecture (Levine, et al., 2019). Here, complexity scales linearly, not exponentially (Huggins, et al., 2018). This enables quantum states across a phase transition to require only a very small training data set (Caro, M., et al., 2022). With the new algorithm, people can learn financial accounting in 10 hours; a process that would take at least one year with the traditional financial paradigm, observed by Luca Pacioli in 1494. Results are based on solid empirical evidence.

Keywords: Tensor Networks, Deep Learning, Computational Complexity, Algorithms, Emergence, Information Reuse, Financial Literacy, Accounting

Suggested Citation

Lacayo Evertsz, Alfredo and Bravo Boza, Lizelia, Deep Learning by a Unitary Tensor Network Algorithm Provides Hyperfast Financial Literacy (January 12, 2020). Available at SSRN: https://ssrn.com/abstract=3518838 or http://dx.doi.org/10.2139/ssrn.3518838

Alfredo Lacayo Evertsz (Contact Author)

Florida International University - College of Business ( email )

University Park
11200 SW 8th Street
Miami, FL 33199
United States

HOME PAGE: http://business.fiu.edu/centers/sbdc/consultants.cfm

Qbit Solutions Research Team ( email )

1951 NW 7th Avenue
Cambridge Innovation Center (CIC)
Miami, FL 33136
United States

HOME PAGE: http://www.qbitsolutions.org

Lizelia Bravo Boza

Qbit Solutions Research Team ( email )

1951 NW 7th Avenue
Cambridge Innovation Center (CIC)
Miami, FL 33136
United States

HOME PAGE: http://www.qbitsolutions.org

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
121
Abstract Views
1,345
Rank
394,107
PlumX Metrics