Anomaly on Superspace of Time Series Data

Capozziello, Salvatore; Pinčák, Richard; Kanjamapornkul, Kabin

doi:10.1515/zna-2017-0274

Cited by 13 publications

(7 citation statements)

References 36 publications

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“…The results of data analysis for the algorithm of (ITD-IMF)chain 1 (6) are shown in Figure 10 and the results for the second algorithm of average tensor network of network correlation matrix is shown in Figure 11. The results of Ising algorithm are shown in Figure 12 and the images generated from tensor network are shown in Figure 13.…”

Section: Results Of Data Analysis Of V3 Loop Time Series Datamentioning

confidence: 99%

“…The new application of modified Khovanov cohomology for biology on a superspace of time series data [6] and Grothendieck spectral sequence [7,8] for biology is related to the mechanism of encoding a human genome by using a general equation [9,10] with genetic code as a boundary condition for gene expression. The interaction between the host cell DNA and the viral HIV RNA induces an infinite Grothendieck spectral sequence of Lax pairs of geneon and retrotransposon pairs with sine-Gordon equation for parasitic state.…”

Section: Introductionmentioning

confidence: 99%

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Forecasting Laurent Polynomial in the Chern–Simons Current of V3 Loop Time Series

2019

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The genetic variation in the V3 loop obstruction component of gp120 HIV glycoprotein is defined as a solitary standing wave function with the transition state between the interaction of wave function in the DNA and RNA hidden states. It is a parasitism co-state generated from the coupling between two pairs of hidden 8 states of Laurent polynomial in the Chern-Simons current of HIV genotypes. A modified Nahm equation for a biology with Lax pairs is defined as the pairs of viral glycoprotein states with the transition between DNA and RNA in the reverse transcription process. The direction in the spinor field with genetic variation in 30 samples of the V3 loop time series with hidden 8 states of Laurent polynomial over the Chern-Simons current is predicted using a support spinor machine and convolutional neural network based on the imaging technique generated from tensor correlation network.We assume that the transcription process from the DNA to RNA and to a protein is a chain with the exact sequence in cohomology theory for biology. We cannot separate the DNA from RNA and the protein. It also happens in the transition state, which means that every state of an amino acid is a mixed state. One amino acid is linked with the other amino acids with an affine Poincare group with modulo SO(3, 1). [40] The derivation of a distribution in gene expression shows us the coupling transition protein states as an interaction of

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Section: Results Of Data Analysis Of V3 Loop Time Series Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Forecasting Laurent Polynomial in the Chern–Simons Current of V3 Loop Time Series

2019

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“…proof: see [13] . We divide market into 2 separated sheet of Dbrane and anti-Dbrane of embedded indifference curve of supply curve and utility curve of demand.…”

Section: Volatility Clustering Phenomena and General Equilibrium Imentioning

confidence: 99%

“…The main problem in FGARCH is an infinite variance and the stylized fact still happens in the form of the power law distribution. With the development of the quantum field theory [6], the Chern-Simons current induced from the interaction of the dark energy in a living organism [7] , loop gravity [8] and some new emerging disciplines such as econophysics [9], complex system [10] and behavior economic theory [11], economists and econophysicists gradually get deeper understanding on the market hidden geometry induced from the interaction of buying and selling orderbook submissions of traders and hidden behavior [12] of traders in financial market [13] which we empirical observed from the financial time series data by using GARCH model [14]. Some experts in the complex system and fractal geometry [15] had been argued that EMH cannot be use to explain some weird phenomena of financial time series, e. g., volatility clustering phenomena.…”

Section: Introductionmentioning

confidence: 99%

GARCH(1,1) Model of the Financial Market with the Minkowski Metric

Pinčák

Kanjamapornkul

2018

Zeitschrift Für Naturforschung A

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We solved a stylized fact on a long memory process of volatility cluster phenomena by using Minkowski metric for GARCH(1,1) under assumption that price and time can not be separated. We provide a Yang-Mills equation in financial market and anomaly on superspace of time series data as a consequence of the proof from the general relativity theory. We used an original idea in Minkowski spacetime embedded in Kolmogorov space in time series data with behavior of traders. The result of this work is equivalent to the dark volatility or the hidden risk fear field induced by the interaction of the behavior of the trader in the financial market panic when the market crashed.

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“…D−brane → O Xt → O Yt → O Xt/Yt → 0 anti−D−brane → O Y * t /X * t → O X * t → O Y * t → 0 D−brane(38) …”

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confidence: 99%

The Chern‐Simons Current in Systems of DNA‐RNA Transcriptions

et al. 2018

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A Chern-Simons current, coming from ghost and anti-ghost fields of supersymmetry theory, can be used to define a spectrum of gene expression in new time series data where a spinor field, as alternative representation of a gene, is adopted instead of using the standard alphabet sequence of bases A, T, C, G, U . After a general discussion on the use of supersymmetry in biological systems, we give examples of the use of supersymmetry for living organism, discuss the codon and anti-codon ghost fields and develop an algebraic construction for the trash DNA, the DNA area which does not seem active in biological systems. As a general result, all hidden states of codon can be computed by Chern-Simons 3 forms. Finally, we plot a time series of genetic variations of viral glycoprotein gene and host T-cell receptor gene by using a gene tensor correlation network related to the Chern-Simons current. An empirical analysis of genetic shift, in host cell receptor genes with separated cluster of gene and genetic drift in viral gene, is obtained by using a tensor correlation plot over time series data derived as the empirical mode decomposition of Chern-Simons current.

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Anomaly on Superspace of Time Series Data

Cited by 13 publications

References 36 publications

Forecasting Laurent Polynomial in the Chern–Simons Current of V3 Loop Time Series

Forecasting Laurent Polynomial in the Chern–Simons Current of V3 Loop Time Series

GARCH(1,1) Model of the Financial Market with the Minkowski Metric

The Chern‐Simons Current in Systems of DNA‐RNA Transcriptions

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