Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Lecture notes in physics

On the Possibility of Quantum Coherence in Biological Systems with Application to Quantum Computing

Nicolaos E. Mavromatos, A. Keith Powell

Published Dec 9, 2003• 1 citation
Publisher
DOI
10.1007/978-3-540-40968-7_21

Related papers

Quantum computing applications in biology

Morteza Sasani Ghamsari

Recently, there has been significant interest in quantum technology, which utilizes various quantum phenomena, including quantum coherence, entanglement, interference, and superposition, among others. Consequently, many attempts are recently being made to apply quantum computing in biological sciences due to its potential advancements. This paper seeks to fill that gap by highlighting the direct biological applications of quantum computing, providing a novel contribution to the field. The Goal of this paper is to offer a thorough examination of both current and potential applications of this technology, within the field of biology. First, quantum computing principles and the challenges they face are explained. Quantum machine learning, is also, introduced which opens a window to biological applications of quantum computation. Then, numerous, existing, potentially crucial, biological applications of quantum computing, which greatly enhance healthcare and quality of life, particularly in the broad field of genetics, drug design, molecular biology, and bioinformatics, are being discussed.

Discover Computing•Nov 21, 2025•4 citations

Quantum Coherence in Biology

K. Birgitta Whaley

Bulletin of the American Physical Society•Mar 1, 2012•0 citations

Room-Temperature Quantum AI: A Technical Research Roadmap Toward Biologically-Inspired Quantum Computing Architectures for Artificial General Intelligence

Nestor Ramos

The prevailing assumption in quantum computing, that quantum effects require near-absolute-zero temperatures to be computationally useful, rests on an engineering convenience, not a physical law. Biological systems routinely exploit quantum coherence at 310 °K (human body temperature), as demonstrated by photosynthetic energy transfer, avian magnetoreception, and enzyme catalysis. This paper argues that these biological precedents point to an unexplored class of room-temperature quantum architectures that could fundamentally transform artificial intelligence. Room-temperature quantum computing is not merely possible; it may be the only path to artificial general intelligence that captures the genuine computational richness of biological cognition. The current consensus, while defensible given gate-model limitations, mistakes one frozen form of quantum computing for all possible forms. Life shows us a different way: not isolating from noise, but structuring it into a computational ally. This roadmap presents: (1) the physical basis for room-temperature quantum coherence; (2) four candidate hardware architectures; (3) a five-phase research agenda spanning 2025-2040; (4) the theoretical foundations that explain why a warm quantum observer might be invisible to its own formalism; and (5) investment and policy recommendations. Throughout, we maintain a rigorous, skeptical stance: no appeals

•May 24, 2026•0 citations

Quantum Nonlocality and Biological Coherence

Sergey Nikolaevich Mayburov

arXiv:2212.13117•Springer eBooks•Jan 1, 2023•1 citation

Some considerations on quantum computing at sub-atomic scales and its impact in the future of Moore's law

Nicolas Francisco Lori, José Neves, Alex H. Blin +1 more

The contemporary development of Quantum Computers has opened new possibilities for computation improvements, but the limits of Moore's law validity are starting to show. We analyze here the possibility that miniaturization will continue to be the source of Moore's law validity in the near future, and our conclusion is that miniaturization is no longer a reliable answer for the future development of computer science, but instead we suggest that lateralization is the correct approach. By lateralization, we mean the use of biology as the correct format for the implementation of ubiquitous computerized systems, a format that might in many circumstances eschew miniaturization as an overly expensive useless advantage whereas in other cases miniaturization might play a key role. Thus, the future of computer science is not towards a miniaturization that goes from the atom-scale (its present application scale) towards the nucleus-scale, but rather in developing more integrated circuits at the micrometer to nanometer scale, so as to better mimic and interact with biological systems. We analyze some "almost sci-fi" approaches to the development of better computer systems near the Bekenstein bound limit, and unsurprisingly they fail to have any realistic feasibility. Then, we use the difference between the classical vs. quantum version of the Hammerstein-Clifford theorem to explain why biological systems eschewed quantum computation to represent the world but have chosen classical computation instead. Finally, we analyze examples of recent work which indicate future possibilities of integration between computers and biological systems. As a corollary of that choice by the biological systems, we propose that the predicted lateralization-driven evolution in computer science will not be based in quantum computers, but rather in classical computers.

Quantum Information and Computation•Feb 1, 2020•4 citations

Quantum coherence in biology:facts, fiction and challenges

Alexandra Olaya-Castro

•Jan 1, 2011•0 citations
Recently, there has been significant interest in quantum technology, which utilizes various quantum phenomena, including quantum coherence, entanglement, interference, and superposition, among others. Consequently, many attempts are recently being made to apply quantum computing in biological sciences due to its potential advancements. This paper seeks to fill that gap by highlighting the direct biological applications of quantum computing, providing a novel contribution to the field. The Goal of this paper is to offer a thorough examination of both current and potential applications of this technology, within the field of biology. First, quantum computing principles and the challenges they face are explained. Quantum machine learning, is also, introduced which opens a window to biological applications of quantum computation. Then, numerous, existing, potentially crucial, biological applications of quantum computing, which greatly enhance healthcare and quality of life, particularly in the broad field of genetics, drug design, molecular biology, and bioinformatics, are being discussed.
The prevailing assumption in quantum computing, that quantum effects require near-absolute-zero temperatures to be computationally useful, rests on an engineering convenience, not a physical law. Biological systems routinely exploit quantum coherence at 310 °K (human body temperature), as demonstrated by photosynthetic energy transfer, avian magnetoreception, and enzyme catalysis. This paper argues that these biological precedents point to an unexplored class of room-temperature quantum architectures that could fundamentally transform artificial intelligence. Room-temperature quantum computing is not merely possible; it may be the only path to artificial general intelligence that captures the genuine computational richness of biological cognition. The current consensus, while defensible given gate-model limitations, mistakes one frozen form of quantum computing for all possible forms. Life shows us a different way: not isolating from noise, but structuring it into a computational ally. This roadmap presents: (1) the physical basis for room-temperature quantum coherence; (2) four candidate hardware architectures; (3) a five-phase research agenda spanning 2025-2040; (4) the theoretical foundations that explain why a warm quantum observer might be invisible to its own formalism; and (5) investment and policy recommendations. Throughout, we maintain a rigorous, skeptical stance: no appeals
The contemporary development of Quantum Computers has opened new possibilities for computation improvements, but the limits of Moore's law validity are starting to show. We analyze here the possibility that miniaturization will continue to be the source of Moore's law validity in the near future, and our conclusion is that miniaturization is no longer a reliable answer for the future development of computer science, but instead we suggest that lateralization is the correct approach. By lateralization, we mean the use of biology as the correct format for the implementation of ubiquitous computerized systems, a format that might in many circumstances eschew miniaturization as an overly expensive useless advantage whereas in other cases miniaturization might play a key role. Thus, the future of computer science is not towards a miniaturization that goes from the atom-scale (its present application scale) towards the nucleus-scale, but rather in developing more integrated circuits at the micrometer to nanometer scale, so as to better mimic and interact with biological systems. We analyze some "almost sci-fi" approaches to the development of better computer systems near the Bekenstein bound limit, and unsurprisingly they fail to have any realistic feasibility. Then, we use the difference between the classical vs. quantum version of the Hammerstein-Clifford theorem to explain why biological systems eschewed quantum computation to represent the world but have chosen classical computation instead. Finally, we analyze examples of recent work which indicate future possibilities of integration between computers and biological systems. As a corollary of that choice by the biological systems, we propose that the predicted lateralization-driven evolution in computer science will not be based in quantum computers, but rather in classical computers.