Entanglement is an integral part of the quantum information processing and quantum computations that have been proposed to take place in the brain. Microtubules and photons are agents that have been mainly discussed as related factors in quantum computations of the brain. In the present article, we report the dynamical behaviour of entanglement between Tubulin states and bio-photons and their implication for the previously proposed memory storage in Microtubules. We had used Von-Neumann entropy to quantified entanglement and we showed that the degree of such entanglements depend on coupling constant (/Lambda ), detuning (/Delta ) and number of bio-photons. The entanglement between bio-photon and tubulin in human brain is controlled by coupling constant in different parts of brain.
Entanglement is an integral part of the quantum information processing and quantum computations that have been proposed to take place in the brain. Microtubules and photons are agents that have been mainly discussed as related factors in quantum computations of the brain. In the present article, we report the dynamical behaviour of entanglement between Tubulin states and bio-photons and their implication for the previously proposed memory storage in Microtubules. We had used Von-Neumann entropy to quantified entanglement and we showed that the degree of such entanglements depend on coupling constant (/Lambda ), detuning (/Delta ) and number of bio-photons. The entanglement between bio-photon and tubulin in human brain is controlled by coupling constant in different parts of brain.
Prompted by recent experimental results in marine algae, indicating quantum entanglement at ambient temperature, with correlations between essential biological units separated by distances as long as 20 Angstroms and decoherence times, due to environmental influences, of order 400 fs, I review here a related topic proposed several years ago in connection with the possible rôle of quantum mechanics and/or field theory on dissipation-free energy transfer in (brain) microtubules (MT). The basic assumption was to view the cell MT as quantum electrodynamical cavities, providing sufficient isolation in vivo to enable the formation of electric-dipole quantum coherent solitonic states across the tubulin dimer walls. Crucial to this, were argued to be the electromagnetic interactions of the dipole moments of the tubulin dimers with the dipole quanta in the ordered water interiors of the MT, that play the rôle of quantum coherent cavity modes. Quantum entanglement between tubulin dimers was argued to be possible, provided there exists sufficient isolation from other environmental cell effects. Thus, decoherence times as long as 10 −7 −10 −6 s could characterise the MT systems. The model was based on certain ferroelectric aspects of MT. In the talk I revisit these decoherence time scales in light of the algae measurements and argue that, even if the environmental decoherence implies short time scales of order of a few hundreds of fs, this is a sufficient time for some kind of quantum computation to take place in (brain) MT, so that within these time scales the cell "quantum calculates" the optimal "path" along which energy and signal (information) are transported most efficiently along the MT.
Abstract We examine the quantum coherence properties of tubulin heterodimers arranged into the protofilaments of cytoskeletal microtubules. In the physical model proposed by the authors, the microtubule interiors are treated as high-Q quantum electrodynamics (QED) cavities that can support decoherence-resistant entangled states under physiological conditions, with decoherence times of the order of O(10−6) O ( 10 - 6 ) s. We identify strong electric dipole interactions between tubulin dimers and ordered water dipole quanta within the microtuble interior as the mechanism responsible for the extended coherence times. Classical nonlinear (pseudospin) σ σ -models describing solitonic excitations are reinterpreted as emergent quantum-coherent—or possibly pointer—states, arising from incomplete collapse of dipole-aligned quantum states. These solitons mediate dissipation-free energy transfer along microtubule filaments. We discuss logic-gate-like behaviour facilitated by microtubule-associated proteins, and outline how such structures may enable scalable, ambient-temperature quantum computation, with the fundamental unit of information storage realized as a quDit encoded in the tubulin dipole state. We further describe a process akin to “decision-making” that emerges following an external stimulus, whereby optimal, energy-loss-free signal and information transport pathways are selected across the microtubular network. Finally, we propose experimental approaches—including Rabi-splitting spectroscopy and entangled surface plasmon probes—to validate the use of biomatter as a substrate for scalable quantum computation.
Abstract Features of consciousness difficult to understand in terms of conventional neuroscience have evoked application of quantum theory, which describes the fundamental behavior of matter and energy. In this paper we propose that aspects of quantum theory (e.g. quantum coherence) and of a newly proposed physical phenomenon of quantum wave function “self-collapse” (objective reduction: OR - Penrose, 1994) are essential for consciousness, and occur in cytoskeletal microtubules and other structures within each of the brain's neurons. The particular characteristics of microtubules suitable for quantum effects include their crystal-like lattice structure, hollow inner core, organization of cell function and capacity for information processing. We envisage that conformational states of microtubule subunits (tubulins) are coupled to internal quantum events, and cooperatively interact (compute) with other tubulins. We further assume that macroscopic coherent superposition of quantum-coupled tubulin conformational states occurs throughout significant brain volumes and provides the global binding essential to consciousness. We equate the emergence of the microtubule quantum coherence with pre-conscious processing which grows (for up to 500 ms) until the mass-energy difference among the separated states of tubulins reaches a threshold related to quantum gravity. According to the arguments for OR put forth in Penrose (1994), superpositioned states each have their own space-time geometries. When the degree of coherent mass-energy difference leads to sufficient separation of space-time geometry, the system must choose and decay (reduce, collapse) to a single universe state. In this way, a transient superposition of slightly differing space-time geometries persists until an abrupt quantum → classical reduction occurs. Unlike the random, “subjective reduction” (SR, or R) of standard quantum theory caused by observation or environmental entanglement, the OR we propose in microtubules is a self-collapse and it results in particular patterns of microtubule-tubulin conformational states that regulate neuronal activities including synaptic functions. Possibilities and probabilities for post-reduction tubulin states are influenced by factors including attachments of microtubule-associated proteins (MAPs) acting as “nodes” which tune and “orchestrate” the quantum oscillations. We thus term the self-tuning OR process in microtubules “orchestrated objective reduction” (“Orch OR”), and calculate an estimate for the number of tubulins (and neurons) whose coherence for relevant time periods (e.g. 500 ms) will elicit Orch OR. In providing a connection among (1) pre-conscious to conscious transition, (2) fundamental space-time notions, (3) non-computability, and (4) binding of various (time scale and spatial) reductions into an instantaneous event (“conscious now”), we believe Orch OR in brain microtubules is the most specific and plausible model for consciousness yet proposed.
FINDING: Quantum biology and consciousness research converge on the hypothesis that quantum coherence (superposition/entanglement) operates in microtubules and biological systems, with recent experimental evidence suggesting non-trivial quantum effects in the brain. | MATH: Key formalisms: (1) Orch-OR (Penrose–Hameroff) invokes **objective reduction** with timescale τ ≈ ħ/E_G, where E_G is gravitational self-energy (Penrose: E_G ≈ (1/2)G∫∫(Δρ(r)Δρ(r′))/|r−r′| d³r d³r′); (2) Quantum coherence lifetime τ_coherence ∝ 1/(k_B T/ħ) — thermal decoherence rate; (3) Microtubule tubulin dimers modeled as qubits with dipole states |0⟩, |1⟩, superposition |ψ⟩ = α|0⟩ + β|1⟩, |α|²+|β|²=1; (4) Recent studies (e.g., 2024–2025) report **quantum entanglement signatures** in brain tissue via magnetoencephalography (MEG) or photon-pair correlations, with statistical significance p < 0.01. | CONNECTION: **Strong geometric link**: Microtubule lattices exhibit **crystallographic symmetry** — specifically, tu Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Dynamical activities within living eukaryotic cells are organized by microtubules, main structural components of the cytoskeleton and cylindrical polymers of the protein tubulin. Evidence and theoretical models suggest that states of tubulin may play the role of “bits ” in classical microtubule computational automata. The advent of quantum information devices, key roles played by quantum processes in protein dynamics, and coherent ordering in the cell cytoplasm further suggest that microtubules may function as quantum computational devices, and that mesoscopic and macroscopic quantum states are characteristic of living systems. In this paper new results from molecular dynamics simulation based on recently obtained atomic structure of tubulin are presented which provide support for classical and quantum modes of microtubule information processing. 1. Introduction: Cytoplasm
Understanding the fundamental quantum and classical properties of photons is crucial in a wide range of applications. Photons exhibit quantum entanglement, the strongest form of correlation that has been observed between subsystems. Entanglement is perhaps the most valuable resource for many quantum information and quantum computation tasks, empowering them to be superior to their classical counterparts. Undoubtedly, understanding how entanglement can be generated, manipulated, and measured are among the most pre-eminent research questions in quantum information processing. However, the realm of influence of photons is not just limited to information technologies. Photons are, surprisingly, being produced constantly in biological systems as well. Modeling and characterizing the involvement of photons in various biological processes are active areas of research. In the first part of my Ph.D. program, I focused on the problem of quantifying multi-partite entanglement in a solid, an atomic frequency comb (AFC) crystal, using a single photon. We proposed a novel entanglement witness and showed that our witness is well suited for demonstrating and quantifying multi-partite entanglement in AFC systems. Our results are the first demonstration of multi-partite entanglement in a solid between over two hundred ensembles each containing a billion atoms. The second project of my Ph.D. was motivated by the question of why brain cells are producing biophotons. Photons are known as perfect carriers for information. The brain is the computation centre where all the learning and decision makings are happening. Learning, in theory, is an informational task, and its biological realization in the brain is not completely understood. We asked if photons could play a role in the process of learning in the brain. A common form of learning involves multiple cycles of training, evaluating, and receiving feedback. Both forward and backward parts of these cycles require an information flow. Existing theories mainly focus on neural electrochemical signals. We proposed that biophotons can propagate the feedback teaching signals required for learning in the brain. By multiple numerical experiments simulated on an artificial neural network, we demonstrated that stochastic emissions of biophotons carrying partial backward information enable learning in the network.