The detection and processing of environmental information is a fundamental attribute of all living systems. This article approaches the question of how efficiently plants process that information, considering it likely that differential efficiency among different species may help explain differential survival. The primary routes of information transfer, that is, signal transduction, are relatively well understood. It is pointed out, based on current understanding, that erasure of such information may be of equal importance to its acquisition. This in turn could provide a simple means of quantifying the acquisition of information by a plant and the efficiency in doing so. However, wild plants live in an environment that is noisy. A useful analogy to deal with such situations can be found in quantum theory of open systems, wherein processes are both well-characterized and well understood, unlike those in plants. This paper develops this theme from quantum information processing and provides a mean of transferring such quantum characterization to biological dynamical situations. The article concludes with discussion on communication theory, indicating that there is a dearth of experimental results that can currently be used to investigate information processing but suggesting how progress can be made in this important programme.
The detection and processing of environmental information is a fundamental attribute of all living systems. This article approaches the question of how efficiently plants process that information, considering it likely that differential efficiency among different species may help explain differential survival. The primary routes of information transfer, that is, signal transduction, are relatively well understood. It is pointed out, based on current understanding, that erasure of such information may be of equal importance to its acquisition. This in turn could provide a simple means of quantifying the acquisition of information by a plant and the efficiency in doing so. However, wild plants live in an environment that is noisy. A useful analogy to deal with such situations can be found in quantum theory of open systems, wherein processes are both well-characterized and well understood, unlike those in plants. This paper develops this theme from quantum information processing and provides a mean of transferring such quantum characterization to biological dynamical situations. The article concludes with discussion on communication theory, indicating that there is a dearth of experimental results that can currently be used to investigate information processing but suggesting how progress can be made in this important programme.
Stochastic Schrödinger equations that govern the dynamics of open quantum systems are given by the equations for signal processing. In particular, the Brownian motion that drives the wave function of the system does not represent noise, but provides purely the arrival of new information. Thus the wave function is guided by the optimal signal detection about the conditions of the environments under noisy observations. This behaviour is similar to biological systems that detect environmental cues, process this information, and adapt to them optimally by minimising uncertainties about the conditions of their environments. It is postulated that information-processing capability is a fundamental law of nature, and hence that models describing open quantum systems can equally be applied to biological systems to model their dynamics. For illustration, simple stochastic models are considered to capture heliotropic and gravitropic motions of plants. The advantage of such dynamical models is that they allow for the quantification of information processed by the plants. By considering the consequence of information erasure, it is argued that biological systems can process environmental signals relatively close to the Landauer limit of computation, and that loss of information must lie at the heart of ageing in biological systems.
Many living organisms can exploit quantum mechanical effects to gain distinct biological advantages. In plants, photosynthesis uses quantum coherence to achieve near 100% efficiency in energy transfer. With advances in experimental techniques, two-dimensional electronic spectroscopy can reveal dynamic processes such as coherence and coupling within a system, and it plays an important role in studying energy transfer in photosynthesis. On the theory side, methods such as the generalized Bloch-Redfield theory and the hierarchical equations of motion are used to model photosynthetic systems. Quantum simulation, as a high-efficiency and low-complexity approach, has also made progress across various platforms in the study of photosynthesis. In recent years, a series of studies has introduced quantum coherence into artificial systems to enhance energy transfer efficiency, laying the groundwork for the design of coherent devices with efficient energy transport. Birds can use the weak geomagnetic field and spin-dependent chemical reactions to detect direction. Theoretical frameworks for animal navigation include magnetite-based mechanisms, magnetoreceptor genes, and the radical-pair mechanism. Quantum simulations of navigation have also advanced on multiple platforms. Inspired by animal navigation, diverse quantum effects have been applied to improve sensing and to support navigation tasks. This paper presents a comprehensive review of progress on quantum coherence in photosynthesis and avian navigation, along with related theoretical methods, quantum simulation approaches, and research on quantum coherent devices.
Understanding how living cells move information and energy so quickly and efficiently is a key question in modern biophysics. In this project, I use quantum-inspired computational models to study cellular signaling networks and energy transfer pathways. The main idea is to treat signaling molecules like “walkers” on a graph and compare how signals spread under classical rules versus quantum-inspired rules. Using Python, I built simple graph-based simulations of signaling and energy transfer. In the quantum-inspired version, nodes can be in superposed states and transitions are probabilistic, similar to quantum walks. I then compared how fast and how reliably signals reach target nodes in the two cases. The results suggest that quantum-inspired dynamics can support faster and more robust signal propagation, echoing coherence effects reported in photosynthetic complexes. I also reviewed recent work in quantum biology, biophotonics, and molecular computation to relate the simulations to real biological systems. Finally, I briefly reflect on ethical and societal questions that arise when quantum ideas are applied to biology and cognition. Overall, the project shows how quantum-inspired models can deepen our understanding of biological communication and open new directions in biomedical engineering and computational science.
Abstract The lines separating Biology and Physics have started to blur in recent decades, leading to the emergence of the interdisciplinary field known as quantum Biology. This field looks into the possibility that basic quantum mechanical phenomena such as coherence, entanglement, tunneling, and superposition play crucial roles in biological processes that are beyond the scope of classical Physics. Biology has traditionally worked within the parameters of classical mechanics, presuming that delicate quantum effects cannot endure in the warm, humid, and cacophonous environments of living systems. But new findings in fields like photosynthesis, olfaction, avian magnetoreception, and enzyme catalysis indicate otherwise, suggesting that living things intentionally and possibly advantageously use quantum principles. From the earliest speculative theories to the most recent experimental confirmations, this book chapter methodically examines the evolution of quantum Biology. We investigate how the exceptionally high energy transfer efficiency in photosynthetic complexes particularly in the light-harvesting proteins of green sulfur bacteria and plants is supported by quantum coherence. The remarkable speed of proton transfers and enzymatic reactions during DNA replication is also investigated in relation to quantum tunneling. The chapter explores magnetoreception in migratory birds and suggests models in which sensitivity to Earth's geomagnetic field is made possible by radical pair mechanisms influenced by quantum entanglement. We also discuss the intriguing but controversial idea that quantum vibrations improve the human olfactory system's capacity for discrimination. In addition to examining particular occurrences, this research challenges more general theoretical models that seek to balance quantum mechanics with the decoherence commonly observed in biological settings. Recent developments in quantum information theory, biomimetic quantum technologies, and ultrafast spectroscopy are highlighted as essential instruments advancing empirical research. We also critically evaluate the field's methodological difficulties, the skepticism of overly optimistic interpretations, and the significant philosophical ramifications of acknowledging life as a quantum phenomenon. In conclusion, quantum Biology suggests that quantum effects are not uncommon aberrations but rather are an essential part of life, offering not only a fresh perspective for reinterpreting well-known biological processes but also the potential for a fundamental paradigm shift. Quantum biology has the potential to completely transform biotechnology, medicine, and our comprehension of consciousness and the origin of life as experimental methods advance. This chapter highlights the significance of interdisciplinary cooperation in order to completely comprehend the latest discoveries and possible future paths of quantum Biology, highlighting its revolutionary influence on our comprehension of life at the most basic levels. Key words: Quantum Biology, tunneling, avian magnetoreception, enzyme catalysis
Quantum sensing uses properties like superposition and entanglement to probe with remarkable sensitivity the properties of a system or its environment. It seems likely that some natural systems have evolved to exploit quantum sensing to help organisms derive information about their ambient conditions. There is also increasing interest in exploiting potential ‘quantum advantage’ in sensing and imaging of biological systems, including in medical diagnostics. There is much debate, however, about how (or even whether) the often weak signals survive complex and noisy biological environments. I will discuss strategies for investigating how any supposed quantum advantage might propagate through a biological system and how nature might have evolved to amplify weak signals.
In the first part of this thesis we extensively review the general theory of open quantum systems. We introduce new approaches to describe, in a hopefully more transparent way, some aspects which are usually misleading in a broad range of the literature. In addition, we revise new concepts and methods developed in recent years that complement the general theory mainly developed in the 1970s. In the second part, we focus our attention on the so-called Markovian processes which have been described in the previous part. We study the validity of typical equations used in simple systems such as harmonic oscillators, and propose and check different strategies to describe Markovian dynamics in more complicated interacting systems. Finally we propose a counter-intuitive situation where some level of noise can be actually useful for information tasks. In the third and last part, we approach the problem of the non-Markovian description of open quantum systems. To quantify how non-Markovian an open quantum system is we introduce a computable measure and apply it to some relevant situations. We also propose a way of probing the complexity of an environment by visualizing properties of a pair of qubits embedded in it. In addition, we develop a technique based on orthogonal polynomial theory to transform a wide range of environments into simple chains of particles which can be efficiently simulated with numerical techniques.