page1 Abstract Dirac notation has been widely used for vectors in Hilbert spaces of Quantum Theories. In this paper, we propose to use the Probability Bracket Notation (PBN), a new set of symbols defined similarly (but not identically) as in Dirac notation. By applying PBN to fundamental definitions and theorems for discrete and continuous random variables, we show that PBN could play a similar role in probability sample space as Dirac notation in Hilbert vector space. Applying PBN to homogeneous Markov chains (MC) with discrete time, we show that our system state P-kets are identified with the probability vectors in Markov chains (MC). Then we apply PBN to general stochastic processes (SP). The master equation of time-continuous homogeneous MC in the Schrodinger pictures is discussed. Our system state P-bra is identified with Doi's state function and Peliti's standard bra. In the end, we investigated the transition of probability density from the Schrodinger picture to the Heisenberg picture for time-continuous homogeneous MC. We
page1 Abstract Dirac notation has been widely used for vectors in Hilbert spaces of Quantum Theories. In this paper, we propose to use the Probability Bracket Notation (PBN), a new set of symbols defined similarly (but not identically) as in Dirac notation. By applying PBN to fundamental definitions and theorems for discrete and continuous random variables, we show that PBN could play a similar role in probability sample space as Dirac notation in Hilbert vector space. Applying PBN to homogeneous Markov chains (MC) with discrete time, we show that our system state P-kets are identified with the probability vectors in Markov chains (MC). Then we apply PBN to general stochastic processes (SP). The master equation of time-continuous homogeneous MC in the Schrodinger pictures is discussed. Our system state P-bra is identified with Doi's state function and Peliti's standard bra. In the end, we investigated the transition of probability density from the Schrodinger picture to the Heisenberg picture for time-continuous homogeneous MC. We
Dirac notation has been widely used for vectors in Hilbert spaces of Quantum Theories and now also in Information Retrieval. In this paper, we propose to use Probability Bracket Notation (PBN) for probability modeling. The new symbols are defined similarly (but not identically) as in Dirac notation. By using PBN to represent fundamental definitions and theorems for discrete and continuous random variables, we show that PBN could play a similar role in probability sample space as Dirac notation in Hilbert space. We also find a close relation between our system state P-kets and probability vectors in Markov chains. In the end, we apply PBN to some important stochastic processes, present the master equation of time-continuous Markov chains in both Schrodinger and Heisenberg pictures. We identify our system state P-bra with Doi's state function and Peliti's standard bra. We summarize the similarities and differences between PBN and Dirac Notation in the two tables of Appendix A.
Inspired by the Dirac notation, a new set of symbols, the Probability Bracket Notation (PBN) is proposed for probability modeling. By applying PBN to discrete and continuous random variables, we show that PBN could play a similar role in probability spaces as the Dirac notation in Hilbert vector spaces. The time evolution of homogeneous Markov chains with discrete-time and continuous-time are discussed in PBN. Our system state p-kets are identified with the probability vectors, while our system state p-bra can be identified with Doi’s state function and Peliti’s standard bra. We also suggest that, by transforming from the Schrodinger picture to the Heisenberg picture, the time-dependence of a system p-ket of a homogeneous MC can be shifted to the observable as a stochastic process. 1.
Following Dirac’s notation in Quantum Mechanics (QM), we propose the Probability Bracket Notation (PBN), by defining a probability-bra (P-bra), P-ket, P-bracket, P-identity, etc. Using the PBN, many formulae, such as normalizations and expectations in systems of one or more random variables, can now be written in abstract basis-independent expressions, which are easy to expand by inserting a proper P-identity. The time evolution of homogeneous Markov processes can also be formatted in such a way. Our system P-kets are identified with probability vectors and our P-bra system is comparable with Doi’s state function or Peliti’s standard bra. In the Heisenberg picture of the PBN, a random variable becomes a stochastic process, and the Chapman–Kolmogorov equations are obtained by inserting a time-dependent P-identity. Also, some QM expressions in Dirac notation are naturally transformed to probability expressions in PBN by a special Wick rotation. Potential applications show the usefulness of the PBN beyond the constrained domain and range of Hermitian operators on Hilbert Spaces in QM all the way to IT.
Following Dirac’s notation in Quantum Mechanics (QM), we propose the Probability Bracket Notation (PBN), by defining a probability-bra (P-bra), P-ket, P-bracket, P-identity, etc…Using the PBN, many formulas, such as normalizations and expectations in systems of one or more random variables, can now be written in abstract basis-independent expressions, easy to expand by inserting a proper P-identity. The time evolution of homogeneous Markov processes can also be formatted in such a way. Our system P-kets are identified with probability vectors and our P-bra system is comparable with Doi’s state function or Peliti’s standard bra. In the Heisenberg picture of the PBN, a random variable becomes a stochastic process, and the Chapman-Kolmogorov equations are obtained by inserting a time-dependent P-identity. Also, some QM expressions in Dirac notation are naturally transformed to probability expressions in PBN by a special Wick rotation. Potential Applications show the usefulness of the PBN beyond the constrained domain and range of Hermitian operators on Hilbert Spaces in QM all the way to IT.
Following the Dirac vector bracket notation (VBN), we proposed the probability bracket notation (PBN) in our previous paper. We mentioned that under the special Wick rotation (imaginary time), a stationary Schrodinger equation in the Hilbert space transforms into the master equation of a microscopic probabilistic process (MPP) in the probability space. In this article, we first study the MPP of the system of a single particle, we show that the energy expectation of the MPP eventually approaches the lowest energy level in its initial condition and its von Neumann entropy finally vanishes. Then we explore the MPP for the quantum system of identical particles in the Fock space, we recover the expected occupation number of particles and the grand partition function in quantum statistics by connecting time with temperature (the Wick-Matsubara relation). We also reproduce the internal energy of an ideal gas in thermodynamics by using the relation. To address the entropy issue and relate the PBN with research topics of statistics in the literature, we express the density operators and the von Neumann entropy in the probability space by using the PBN. The Wick-Matsubara relation plus the PBN might provide a new way of microscopic probability modeling.
In this article, we continue to explore Probability Bracket Notation (PBN), proposed in our previous article. Using both Dirac vector bracket notation (VBN) and PBN, we define induced Hilbert space and induced sample space, and propose that there exists an equivalence relation between a Hilbert space and a sample space constructed from the same base observable(s). Then we investigate Markov transition matrices and their eigenvectors to make diffusion maps with two examples: a simple graph theory example, to serve as a prototype of bidirectional transition operator; a famous text document example in IR literature, to serve as a tutorial of diffusion map in text document space. We show that the sample space of the Markov chain and the Hilbert space spanned by the eigenvectors of the transition matrix are not equivalent. At the end, we apply our PBN and equivalence proposal to Thermophysics by associating sample (phase) space with the Hilbert space of a single particle and the Fock space of many-particle systems.