Quantum Probability Outside of Physics: from Molecular Biology to Cognition

Masanari Asano, Masanori Ohya, Yoshiharu Tanaka +3 more

Masanari Asano, Irina Basieva, Andrei Yu. Khrennikov +3 more

Masanari Asano, Andrei Yu. Khrennikov, Masanori Ohya +2 more

Arthur I. Fine

Andrei Yu. Khrennikov

Recently, the methods of quantum theory (QT), especially quantum information and probability, started to be widely applied outside of physics: in cognitive, social and political sciences, psychology, economics, finances, decision making, molecular biology and genetics. Such models can be called quantum-like, in contrast to real quantum physical cognitive and biological models. Quantum-like means that only the information and probability structures of QT are explored. This approach matches the information interpretation of QT well (e.g., Zeilinger and Brukner, Fuchs and Mermin, D’Ariano), as well as the informational viewpoint on physics in general (e.g., Wheeler’s “it from bit” paradigm). In this paper, we propose a quantum-like model of an information laser by precessing the assumptions on the structure of state spaces of information processors, “information atoms” (i-atoms) and information fields. The basic assumption is the discrete structure of state spaces related to quantization of an information analog of energy. To analyze a possible structure of the state space of i-atoms leading to the possibility to create information lasers, we have to develop a purely information version of quantum thermodynamics. We did this by placing the main attention on the derivation of the conditions for the equilibrium of information exchange between i-atoms and a quantized information field.

Wei Wu, Jianhua Zhu, Yong Yao +1 more

Recently, quantum biology and molecular quantum computation have attracted substantial attention. Quantum biology applies quantum mechanics to biological systems at the molecular scale. Molecular quantum computing explores the degrees of freedom of molecules that can be used to produce quantum coherence, such as charge, orbital, opto-spin (interplay between optical excitation and spin), vibration, and rotation, to process quantum information. Cognitive science focuses on understanding how learning processes are realized, particularly within the human brain. The most common topic among these three is the computational process, which can exploit different levels of representation, either classical or quantum. Here, we review progress in quantum biology, molecular quantum computing, and quantum theory in cognitive science. Based on our critical analysis and review, we highlight that molecular quantum computing could be an important bridging research area between quantum biology and a deeper understanding of neuronal cells in cognitive science. Thus, these three areas can be the core to understanding how the classical world emerges from the quantum world and human intelligence. To answer these questions, we may gain insight by studying the quantum processes that underlie biological systems, such as photosynthesis and enzyme catalysis. An unprecedented opportunity for molecular quantum computing is to perform functionalities similar to those of the human brain. In this manner, we could not only expand the boundaries for quantum computing but also gain a better understanding of cognitive processes.