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

Quantum Artificial Life Takes Its First Step on an IBM Quantum Computer

inquantio

Published Jul 21, 2026• 0 citations
Publisher

Abstract

A research team based in Spain modeled the four ingredients of Darwinian evolution, self replication, mutation, interaction between individuals, and death, as a quantum circuit and ran it for the first time on IBM's cloud quantum computer, ibmqx4. Each individual was defined as two qubits, a genotype and a phenotype, and successive generations were linked by partial quantum cloning, a procedure that works around the no cloning theorem. The complete model combining all four ingredients reproduced the ideal probability distribution with a fidelity of 93.94%, though the researchers were explicit that this is a proof of principle, a simulation of the logic of life on quantum hardware rather than an account of how life began. [Quantum Biology Society] Where quantum biology has mostly gone looking for quantum mechanical phenomena inside living organisms, this study runs the argument in the opposite direction: it implements the logic of biological evolution inside the physical environment of a quantum computer. The authors describe their line of work as quantum biomimetics, the design of quantum algorithms that imitate biological processes. Researchers at the University of the Basque Country (UPV/EHU) in Bilbao, together with colleagues at several partner institutions, designed the elements of Darwinian natural selection and evolution (self replication, mutation, interaction, and death) as a quantum algorithm that works around the no cloning theorem, one of the founding principles of quantum mechanics. They then succeeded in running it on ibmqx4, the five qubit superconducting chip IBM makes available over the cloud, putting into practice a model the same group had proposed two years earlier. The results, published in Scientific Reports in 2018, stand as the first experimental implementation of a quantum artificial life algorithm on quantum hardware. ■ Two Qubits per Individual: Partial Quantum Cloning Sidesteps the No Cloning Theorem The smallest unit of life in this model, the individual, is built from two qubits, one holding the genotype and one the phenotype. The genotype carries the information that identifies the type of living unit and is handed on from generation to generation. The phenotype is set by the genetic information together with the interaction between the individual and its environment, and that state, along with the information it encodes, is degraded over the individual's lifetime, which is how aging and death enter the model. Self replication, the core of life, is implemented through partial quantum cloning. Quantum mechanics forbids making a perfect copy of an unknown quantum state in full, but it does permit the expectation value of a single chosen observable, here the Pauli Z observable σz, to be written into a blank qubit. Using controlled NOT (CNOT) gates, the researchers passed that particular piece of the genotype's information first into the genotype qubit of the next generation and then into its phenotype qubit, completing a system of heredity in the quantum world. ■ A Practical Compromise with the Hardware: Emulating Dissipation and Mutation Because the flexibility of current quantum hardware is limited, death and mutation had to be simulated by practical approximations. Death should be produced by leaving the phenotype qubit open to its environment so that its information gradually dissipates, but the device could not perform the conditional projection of the phenotype onto the |0⟩ state that this calls for. Instead the researchers applied a sequence of small rotations about the σy axis, one for each simulated time step, to imitate the running out of a lifetime. As they note, this replaces the dissipation with a discrete process and loses its exponential character. Mutation, likewise, was not implemented as a fully random rotation. The researchers fixed the mutation to a single bit flip (σx) and then took a statistical detour: circuits with and without a mutation were run different numbers of times and the data merged afterward so that the intended mutation rate came out of the aggregate. Interaction between individuals is a conditional operation that swaps phenotypes according to the genotypes, and it was built by combining two qubit gates including CNOT, SWAP, and the controlled square root of NOT. ■ The Results, and the Mutation Paradox The experiments proceeded by adding the elements of evolution one after another: interaction between individuals, self replication, dissipation into the environment, and mutation. For the complete model with all four in place, the measured probability distribution matched the ideal prediction with a fidelity of 93.94%. One result along the way was especially curious. When mutation, the element that injects randomness into the system, was included, the fidelity of the data went up rather than down. The researchers give a level headed account of it: mutations tend to homogenize the probability distribution, which is the same effect the errors already present in the experimental platform produce. They also remark on the intriguing parallel with the classical world, where mutation likewise helps a species adapt to changing environments. ■ What Is Actually Quantum Here: Entanglement That Remembers a Lineage The simpler statistical indicators can be reproduced by a classical computer model without much difficulty. Every indicator based on measurements in the σz basis, the researchers point out, can be matched by a classical probability distribution. So which part of this model is genuinely quantum? The answer shows up in the correlations. A partial quantum cloning operation entangles the qubits it involves, carrying the expectation value of σx in the original state into the joint value of σx⊗σx. In a simplified case without mutations or interactions between individuals, measuring σx⊗σx⊗σx⊗σx across the four qubits of two individuals gives α if the two are linked by a self replication event, and α² if they are not causally connected, where α is the expectation value of σx in the precursor genotype. The two histories are therefore distinguishable from the correlation alone. Had the precursor genotype been a classical incoherent mixture instead, that expectation value would be zero and nothing would propagate into these global correlations at all. In other words, without keeping a separate ledger of who descended from whom, as a classical model would have to, the entangled state of the individuals itself records and attests to the lineage. On the chip this signature survived only in part: the measured value of σx⊗σx⊗σx⊗σx was 0.22 against an ideal 0.56, a sizable error. It was nonetheless clearly different from the product of the correlations within each individual taken separately, which comes out at zero, and it is that difference which shows the two individuals to be causally related. ■ Significance and Limits The study is a well executed proof of principle that a microscopic quantum system can hold the grammar of Darwinian evolution consistently, and that it can be run on a real superconducting quantum chip. The paper is explicit, however, that it is not an observation of quantum effects at work in a living organism. The authors leave open the philosophical question of whether the origin of life is genuinely quantum mechanical, and they state that the quantum supremacy referred to in the abstract and conclusion was not achieved in this experiment but remains a target to be explored on larger quantum computers in the future. They also acknowledge that the part of the dynamics carried by σz, which encodes the lifetime and the predator prey character of an individual, is classical information that a simpler classical analogue could predict; what the classical version cannot supply is the entanglement linking the living units. In asking whether the logic of life can be recoded in the language of quantum mechanics, this work sets out another blueprint for where quantum algorithms and the biological sciences may converge. #QuantumBiology #QuantumComputer #IBMQuantumComputer #QuantumArtificialLife #ArtificialLife #Qubit #QuantumEntanglement #NoCloningTheorem #DarwinianEvolution https://www.nature.com/articles/s41598-018-33125-3

DOI
10.5281/zenodo.21469160

Related papers

Quantum Artificial Life in an IBM Quantum Computer

Unai Alvarez-Rodriguez, Mikel Sanz, Lucas Lamata +1 more

We present the first experimental realization of a quantum artificial life algorithm in a quantum computer. The quantum biomimetic protocol encodes tailored quantum behaviors belonging to living systems, namely, self-replication, mutation, interaction between individuals, and death, into the cloud quantum computer IBM ibmqx4. In this experiment, entanglement spreads throughout generations of individuals, where genuine quantum information features are inherited through genealogical networks. As a pioneering proof-of-principle, experimental data fits the ideal model with accuracy. Thereafter, these and other models of quantum artificial life, for which no classical device may predict its quantum supremacy evolution, can be further explored in novel generations of quantum computers. Quantum biomimetics, quantum machine learning, and quantum artificial intelligence will move forward hand in hand through more elaborate levels of quantum complexity.

arXiv:1711.09442•Scientific Reports•Sep 28, 2018•83 citations

Artificial Life in Quantum Technologies

Unai Alvarez-Rodriguez, Mikel Sanz, Lucas Lamata +1 more

We develop a quantum information protocol that models the biological behaviours of individuals living in a natural selection scenario. The artificially engineered evolution of the quantum living units shows the fundamental features of life in a common environment, such as self-replication, mutation, interaction of individuals, and death. We propose how to mimic these bio-inspired features in a quantum-mechanical formalism, which allows for an experimental implementation achievable with current quantum platforms. This study paves the way for the realization of artificial life and embodied evolution with quantum technologies.

arXiv:1505.03775•Scientific Reports•Feb 8, 2016•29 citations

Προσομοίωση τεχνητής ζωής σε κβαντικό υπολογιστή

Μενέλαος Κουσουνής

The subject of this bachelor thesis is Artificial Life. Moreover, the living organisms (individuals) and the different stages (processes) that constitute the Darwinian evolution, are being expressed using quantum mechanics terms. The acquired model is then realized in the IBM cloud computing environment (IBM Quantum Experience) and the experimental process is conducted to extract specific results. For each distinct process, at least one quantum circuit is built and then sent to a real quantum system. The obtained data are then compared to the ones that are mentioned in the reference paper to confirm their validity, and to the ideal ones (also mentioned in the paper we used as reference) to determine the model’s efficacy. Finally, we propose a modification to the current model, with the ultimate goal being the independence of an individual’s genetically coded lifespan, and its trophic level.

•Mar 4, 2021•0 citations

Recombining Genes with Quantum Computing… Development of the Quantum Biological Block (BioBloQu) Algorithm

inquantio

A study published on bioRxiv demonstrates the first hybrid quantum computing framework combining classical Hamming distance filtering with the Grover quantum search algorithm to overcome bottlenecks in massive genomic data analysis. Utilizing the IBM Qiskit 27-qubit simulator, researchers rapidly and flawlessly identified a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database, even under conditions allowing up to a 30% mismatch. The study lays a revolutionary foundation for synthetic genome design by completing simulations that precisely insert a "BioBloQu" (quantum biological block)—composed of a promoter, an RBS, an enzyme, and a terminator—into the explored scar regions of the minimal genome M. mycoides JCVI-Syn3B. [Quantum Biology Society] Modern life sciences are pouring out genomic sequencing data at an exponential rate. However, due to the immense complexity of biological data, existing classical computing methods are facing severe computational bottlenecks in analyzing and manipulating it. To break through these limitations, a disruptive study recently published on the preprint repository bioRxiv, titled "Genetic Engineering with Quantum Circuits: creating codes and studying BioBloQu genetic elements," has brought quantum computers to the forefront of genetic engineering. A joint research team led by Professor Elibio Rech from the Brazilian Agricultural Research Corporation (Embrapa) Genetic Resources and Biotechnology and the Federal University of Rio Grande do Sul (UFRGS) presented this innovative research. ■ Scanning Massive Genomic Databases with Qubits Using the core quantum mechanical principles of superposition and entanglement as the foundation for information processing, the research team developed a hybrid quantum framework that combines classical Hamming distance filtering with the Grover quantum search algorithm. Powered by IBM's Qiskit 27-qubit simulator, this algorithm was used to search for a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database. As a result, the team successfully and swiftly identified the massive genetic data through amplitude amplification, filtering out the sequence perfectly even under conditions allowing up to a 30% mismatch rate. This proves that vast amounts of genetic data, which are unmanageable for classical computers, can be analyzed in a flash through quantum parallel processing. ■ The Era of Synthetic Genome Design Opened by BioBloQu Furthermore, the researchers successfully completed a quantum circuit simulation that accurately inserts a synthetic genetic construct called "BioBloQu" (quantum biological block) into the identified target regions. In the genome of M. mycoides JCVI-Syn3B, an artificially synthesized minimal genome model, the quantum algorithm first identified two 20-nucleotide "scar" regions—which are traces of gene editing. Then, it precisely integrated a tandem genetic block (BioBloQu) composed of a promoter, a ribosome binding site (RBS), an enzyme sequence, and a terminator into that location. This innovative approach goes beyond simply cutting and pasting existing genes physicochemically; it opens up the possibility of designing and assembling novel synthetic genomes from the ground up under the control of quantum algorithms equipped with overwhelming computational power. By directly applying the computational power of quantum mechanics to biotechnology, this research is expected to serve as the starting point for a massive revolution in next-generation quantum-bio data manipulation, customized gene therapy, and synthetic biology. #QuantumComputing #GeneticRecombination #BioBloQu #QuantumAlgorithm #GroverAlgorithm #Metagenome #SyntheticBiology #GenomeDesign #QuantumBiology #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2025.05.02.651535v2

•Jul 10, 2026•0 citations

Finding DNA Sequences with Quantum Computers... Development of a 'Quantum Algorithm' for Genetic Engineering

inquantio

• Development of the quantum algorithm 'QuBio.py' for searching and analyzing genetic information. • Successful detection of a 50-nucleotide target sequence within a 3,022-nucleotide database using a 127-qubit simulator on the IBM quantum platform. • Securing flexibility that allows up to a 30% mismatch rate... Heralding a new horizon for synthetic biology and new drug development. [Quantum Biology Society] A "quantum computing"-based gene search algorithm has emerged, capable of analyzing exponentially increasing biological data at ultra-high speeds, surpassing the limitations of conventional computers. A study titled "GENETIC ENGINEERING THROUGH QUANTUM CIRCUITS: CONSTRUCTION OF CODES AND ANALYSIS OF GENETIC ELEMENTS BIOBLOQU" was recently published on bioRxiv, a preprint repository for biological sciences. The research team, including Patrícia Verdugo Pascoal, presented an innovative model that explores and manipulates genetic information utilizing quantum mechanics. ■ Translating the Four DNA Bases into Quantum Language... The Evolution of 'Grover's Algorithm' Modern biology generates approximately 1 Gb of sequencing data per hour, but analyzing this data using classical computing methods faces significant limitations. Existing database search methods require computation time proportional to the data size (O(N)), but the quantum-based 'Grover's algorithm' applied by the researchers can significantly reduce this to the O(√N}) level. In particular, a key feature of this study is that it adapted the algorithm to process the four nucleotides (A, T, G, C) that make up DNA, rather than simple binary symbols, thereby enabling it to operate efficiently on more complex datasets. ■ Detecting the Cas9 Target Sequence with 127 Qubits... Creation of Synthetic Genome (BioBloQu) Based on the 127-qubit simulator of the IBM cloud platform, the research team developed its own quantum algorithm code named 'QuBio.py'. Through this algorithm, they succeeded in finding a specific 50-nucleotide target DNA sequence within a genetic database consisting of up to 3,022 nucleotides. A conserved functional domain of the Cas9-like nucleotide sequence found in Brazilian biomes was used as the target sequence. Notably, this quantum algorithm permits a mismatch rate of up to 30% during the sequence comparison process. This enables flexible and rapid analysis in situations where sequence variations are expected, such as homologous gene analysis or evolutionary studies. Furthermore, based on these search results, the team succeeded in constructing a synthetic structure called a 'Quantum Biological Block (BioBloQu)' inside minimal cells (JCVI-syn3.0). The researchers stated that this algorithm "constitutes a unique starting point for developing a more sophisticated model for the manipulation of data". They also predicted that "the integration of quantum computing with artificial intelligence represents an attractive avenue... By optimizing genetic algorithms and facilitating real-time data analyses, quantum computing can revolutionize trait discovery processes in agriculture and biotechnology". This achievement is evaluated as an important example demonstrating how quantum computing can contribute to next-generation synthetic biology technologies that analyze large-scale genetic big data and design genomes from the bottom up.

•Jul 13, 2026•0 citations

Unraveling the Mysteries of Quantum Mechanics… The Encounter Between 'Quantum Darwinism' and Biology

inquantio

∙ Quanta Magazine analyzes the principles of macroscopic world formation through quantum decoherence and quantum Darwinism. ∙ 'Einselection' fixes specific quantum states… similar to how life preserves information. ∙ Integrating quantum biology from physical and philosophical perspectives, redefining the fundamental principles of life's information processing. [Quantum Biology Society] An in-depth analysis has been proposed on how the bizarre phenomena of quantum mechanics transform into the solid macroscopic reality we observe, and what connection this process has with the evolution of life. Recently, the science media outlet Quanta Magazine reported through a contribution by renowned science writer Philip Ball that the theories of 'Quantum Darwinism' and 'Decoherence,' pioneered by physicist Wojciech Zurek, are the key to connecting biological systems with the macroscopic world. ■ The Reality of 'Survival of the Fittest' Created by 'Einselection' In the quantum realm, particles can exist in multiple states simultaneously (superposition), but in the macroscopic world we observe, they appear in only one definite state. According to Dr. Zurek's theory, this happens because quantum systems continuously interact with their surrounding environment, undergoing a process of 'decoherence' where information is dissipated. The core of this process is 'Einselection' (Environment-Induced Superselection). The environment does not accommodate all states; instead, it selects only the most stable and predictable states, known as 'pointer states,' and replicates them innumerably within the environment. Just as only the genetic information advantageous for survival is passed on and spreads in natural selection, the essence of 'Quantum Darwinism' is that quantum information also undergoes a 'survival of the fittest' process dictated by the environment. This ultimately forms an objective macroscopic reality that all of us can commonly perceive. ■ Life, a Product of Evolution that Anchors Quantum Information into Reality Philip Ball noted that these physical principles are strikingly similar to the way biological systems process information. He explains that the vital activities of living organisms—such as recognizing external stimuli, preserving genetic information, and controlling complex metabolic processes—are fundamentally the very processes of filtering meaningful information from quantum superpositions and anchoring them into the physical states of the real world. This report suggests that quantum biology is not merely a discipline that investigates microscopic reactions within cells. Rather, it is a grand unified theory explaining how life has utilized the universe's fundamental principles to process information and evolve. Built upon the theories of Dr. Zurek, a master of modern physics, this analysis presents a new philosophical and physical paradigm that views life as a cosmic entity where matter, information, and quantum mechanics are perfectly integrated.

•Jul 13, 2026•0 citations
A research team based in Spain modeled the four ingredients of Darwinian evolution, self replication, mutation, interaction between individuals, and death, as a quantum circuit and ran it for the first time on IBM's cloud quantum computer, ibmqx4. Each individual was defined as two qubits, a genotype and a phenotype, and successive generations were linked by partial quantum cloning, a procedure that works around the no cloning theorem. The complete model combining all four ingredients reproduced the ideal probability distribution with a fidelity of 93.94%, though the researchers were explicit that this is a proof of principle, a simulation of the logic of life on quantum hardware rather than an account of how life began. [Quantum Biology Society] Where quantum biology has mostly gone looking for quantum mechanical phenomena inside living organisms, this study runs the argument in the opposite direction: it implements the logic of biological evolution inside the physical environment of a quantum computer. The authors describe their line of work as quantum biomimetics, the design of quantum algorithms that imitate biological processes. Researchers at the University of the Basque Country (UPV/EHU) in Bilbao, together with colleagues at several partner institutions, designed the elements of Darwinian natural selection and evolution (self replication, mutation, interaction, and death) as a quantum algorithm that works around the no cloning theorem, one of the founding principles of quantum mechanics. They then succeeded in running it on ibmqx4, the five qubit superconducting chip IBM makes available over the cloud, putting into practice a model the same group had proposed two years earlier. The results, published in Scientific Reports in 2018, stand as the first experimental implementation of a quantum artificial life algorithm on quantum hardware. ■ Two Qubits per Individual: Partial Quantum Cloning Sidesteps the No Cloning Theorem The smallest unit of life in this model, the individual, is built from two qubits, one holding the genotype and one the phenotype. The genotype carries the information that identifies the type of living unit and is handed on from generation to generation. The phenotype is set by the genetic information together with the interaction between the individual and its environment, and that state, along with the information it encodes, is degraded over the individual's lifetime, which is how aging and death enter the model. Self replication, the core of life, is implemented through partial quantum cloning. Quantum mechanics forbids making a perfect copy of an unknown quantum state in full, but it does permit the expectation value of a single chosen observable, here the Pauli Z observable σz, to be written into a blank qubit. Using controlled NOT (CNOT) gates, the researchers passed that particular piece of the genotype's information first into the genotype qubit of the next generation and then into its phenotype qubit, completing a system of heredity in the quantum world. ■ A Practical Compromise with the Hardware: Emulating Dissipation and Mutation Because the flexibility of current quantum hardware is limited, death and mutation had to be simulated by practical approximations. Death should be produced by leaving the phenotype qubit open to its environment so that its information gradually dissipates, but the device could not perform the conditional projection of the phenotype onto the |0⟩ state that this calls for. Instead the researchers applied a sequence of small rotations about the σy axis, one for each simulated time step, to imitate the running out of a lifetime. As they note, this replaces the dissipation with a discrete process and loses its exponential character. Mutation, likewise, was not implemented as a fully random rotation. The researchers fixed the mutation to a single bit flip (σx) and then took a statistical detour: circuits with and without a mutation were run different numbers of times and the data merged afterward so that the intended mutation rate came out of the aggregate. Interaction between individuals is a conditional operation that swaps phenotypes according to the genotypes, and it was built by combining two qubit gates including CNOT, SWAP, and the controlled square root of NOT. ■ The Results, and the Mutation Paradox The experiments proceeded by adding the elements of evolution one after another: interaction between individuals, self replication, dissipation into the environment, and mutation. For the complete model with all four in place, the measured probability distribution matched the ideal prediction with a fidelity of 93.94%. One result along the way was especially curious. When mutation, the element that injects randomness into the system, was included, the fidelity of the data went up rather than down. The researchers give a level headed account of it: mutations tend to homogenize the probability distribution, which is the same effect the errors already present in the experimental platform produce. They also remark on the intriguing parallel with the classical world, where mutation likewise helps a species adapt to changing environments. ■ What Is Actually Quantum Here: Entanglement That Remembers a Lineage The simpler statistical indicators can be reproduced by a classical computer model without much difficulty. Every indicator based on measurements in the σz basis, the researchers point out, can be matched by a classical probability distribution. So which part of this model is genuinely quantum? The answer shows up in the correlations. A partial quantum cloning operation entangles the qubits it involves, carrying the expectation value of σx in the original state into the joint value of σx⊗σx. In a simplified case without mutations or interactions between individuals, measuring σx⊗σx⊗σx⊗σx across the four qubits of two individuals gives α if the two are linked by a self replication event, and α² if they are not causally connected, where α is the expectation value of σx in the precursor genotype. The two histories are therefore distinguishable from the correlation alone. Had the precursor genotype been a classical incoherent mixture instead, that expectation value would be zero and nothing would propagate into these global correlations at all. In other words, without keeping a separate ledger of who descended from whom, as a classical model would have to, the entangled state of the individuals itself records and attests to the lineage. On the chip this signature survived only in part: the measured value of σx⊗σx⊗σx⊗σx was 0.22 against an ideal 0.56, a sizable error. It was nonetheless clearly different from the product of the correlations within each individual taken separately, which comes out at zero, and it is that difference which shows the two individuals to be causally related. ■ Significance and Limits The study is a well executed proof of principle that a microscopic quantum system can hold the grammar of Darwinian evolution consistently, and that it can be run on a real superconducting quantum chip. The paper is explicit, however, that it is not an observation of quantum effects at work in a living organism. The authors leave open the philosophical question of whether the origin of life is genuinely quantum mechanical, and they state that the quantum supremacy referred to in the abstract and conclusion was not achieved in this experiment but remains a target to be explored on larger quantum computers in the future. They also acknowledge that the part of the dynamics carried by σz, which encodes the lifetime and the predator prey character of an individual, is classical information that a simpler classical analogue could predict; what the classical version cannot supply is the entanglement linking the living units. In asking whether the logic of life can be recoded in the language of quantum mechanics, this work sets out another blueprint for where quantum algorithms and the biological sciences may converge. #QuantumBiology #QuantumComputer #IBMQuantumComputer #QuantumArtificialLife #ArtificialLife #Qubit #QuantumEntanglement #NoCloningTheorem #DarwinianEvolution https://www.nature.com/articles/s41598-018-33125-3
We present the first experimental realization of a quantum artificial life algorithm in a quantum computer. The quantum biomimetic protocol encodes tailored quantum behaviors belonging to living systems, namely, self-replication, mutation, interaction between individuals, and death, into the cloud quantum computer IBM ibmqx4. In this experiment, entanglement spreads throughout generations of individuals, where genuine quantum information features are inherited through genealogical networks. As a pioneering proof-of-principle, experimental data fits the ideal model with accuracy. Thereafter, these and other models of quantum artificial life, for which no classical device may predict its quantum supremacy evolution, can be further explored in novel generations of quantum computers. Quantum biomimetics, quantum machine learning, and quantum artificial intelligence will move forward hand in hand through more elaborate levels of quantum complexity.
We develop a quantum information protocol that models the biological behaviours of individuals living in a natural selection scenario. The artificially engineered evolution of the quantum living units shows the fundamental features of life in a common environment, such as self-replication, mutation, interaction of individuals, and death. We propose how to mimic these bio-inspired features in a quantum-mechanical formalism, which allows for an experimental implementation achievable with current quantum platforms. This study paves the way for the realization of artificial life and embodied evolution with quantum technologies.
The subject of this bachelor thesis is Artificial Life. Moreover, the living organisms (individuals) and the different stages (processes) that constitute the Darwinian evolution, are being expressed using quantum mechanics terms. The acquired model is then realized in the IBM cloud computing environment (IBM Quantum Experience) and the experimental process is conducted to extract specific results. For each distinct process, at least one quantum circuit is built and then sent to a real quantum system. The obtained data are then compared to the ones that are mentioned in the reference paper to confirm their validity, and to the ideal ones (also mentioned in the paper we used as reference) to determine the model’s efficacy. Finally, we propose a modification to the current model, with the ultimate goal being the independence of an individual’s genetically coded lifespan, and its trophic level.
A study published on bioRxiv demonstrates the first hybrid quantum computing framework combining classical Hamming distance filtering with the Grover quantum search algorithm to overcome bottlenecks in massive genomic data analysis. Utilizing the IBM Qiskit 27-qubit simulator, researchers rapidly and flawlessly identified a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database, even under conditions allowing up to a 30% mismatch. The study lays a revolutionary foundation for synthetic genome design by completing simulations that precisely insert a "BioBloQu" (quantum biological block)—composed of a promoter, an RBS, an enzyme, and a terminator—into the explored scar regions of the minimal genome M. mycoides JCVI-Syn3B. [Quantum Biology Society] Modern life sciences are pouring out genomic sequencing data at an exponential rate. However, due to the immense complexity of biological data, existing classical computing methods are facing severe computational bottlenecks in analyzing and manipulating it. To break through these limitations, a disruptive study recently published on the preprint repository bioRxiv, titled "Genetic Engineering with Quantum Circuits: creating codes and studying BioBloQu genetic elements," has brought quantum computers to the forefront of genetic engineering. A joint research team led by Professor Elibio Rech from the Brazilian Agricultural Research Corporation (Embrapa) Genetic Resources and Biotechnology and the Federal University of Rio Grande do Sul (UFRGS) presented this innovative research. ■ Scanning Massive Genomic Databases with Qubits Using the core quantum mechanical principles of superposition and entanglement as the foundation for information processing, the research team developed a hybrid quantum framework that combines classical Hamming distance filtering with the Grover quantum search algorithm. Powered by IBM's Qiskit 27-qubit simulator, this algorithm was used to search for a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database. As a result, the team successfully and swiftly identified the massive genetic data through amplitude amplification, filtering out the sequence perfectly even under conditions allowing up to a 30% mismatch rate. This proves that vast amounts of genetic data, which are unmanageable for classical computers, can be analyzed in a flash through quantum parallel processing. ■ The Era of Synthetic Genome Design Opened by BioBloQu Furthermore, the researchers successfully completed a quantum circuit simulation that accurately inserts a synthetic genetic construct called "BioBloQu" (quantum biological block) into the identified target regions. In the genome of M. mycoides JCVI-Syn3B, an artificially synthesized minimal genome model, the quantum algorithm first identified two 20-nucleotide "scar" regions—which are traces of gene editing. Then, it precisely integrated a tandem genetic block (BioBloQu) composed of a promoter, a ribosome binding site (RBS), an enzyme sequence, and a terminator into that location. This innovative approach goes beyond simply cutting and pasting existing genes physicochemically; it opens up the possibility of designing and assembling novel synthetic genomes from the ground up under the control of quantum algorithms equipped with overwhelming computational power. By directly applying the computational power of quantum mechanics to biotechnology, this research is expected to serve as the starting point for a massive revolution in next-generation quantum-bio data manipulation, customized gene therapy, and synthetic biology. #QuantumComputing #GeneticRecombination #BioBloQu #QuantumAlgorithm #GroverAlgorithm #Metagenome #SyntheticBiology #GenomeDesign #QuantumBiology #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2025.05.02.651535v2
• Development of the quantum algorithm 'QuBio.py' for searching and analyzing genetic information. • Successful detection of a 50-nucleotide target sequence within a 3,022-nucleotide database using a 127-qubit simulator on the IBM quantum platform. • Securing flexibility that allows up to a 30% mismatch rate... Heralding a new horizon for synthetic biology and new drug development. [Quantum Biology Society] A "quantum computing"-based gene search algorithm has emerged, capable of analyzing exponentially increasing biological data at ultra-high speeds, surpassing the limitations of conventional computers. A study titled "GENETIC ENGINEERING THROUGH QUANTUM CIRCUITS: CONSTRUCTION OF CODES AND ANALYSIS OF GENETIC ELEMENTS BIOBLOQU" was recently published on bioRxiv, a preprint repository for biological sciences. The research team, including Patrícia Verdugo Pascoal, presented an innovative model that explores and manipulates genetic information utilizing quantum mechanics. ■ Translating the Four DNA Bases into Quantum Language... The Evolution of 'Grover's Algorithm' Modern biology generates approximately 1 Gb of sequencing data per hour, but analyzing this data using classical computing methods faces significant limitations. Existing database search methods require computation time proportional to the data size (O(N)), but the quantum-based 'Grover's algorithm' applied by the researchers can significantly reduce this to the O(√N}) level. In particular, a key feature of this study is that it adapted the algorithm to process the four nucleotides (A, T, G, C) that make up DNA, rather than simple binary symbols, thereby enabling it to operate efficiently on more complex datasets. ■ Detecting the Cas9 Target Sequence with 127 Qubits... Creation of Synthetic Genome (BioBloQu) Based on the 127-qubit simulator of the IBM cloud platform, the research team developed its own quantum algorithm code named 'QuBio.py'. Through this algorithm, they succeeded in finding a specific 50-nucleotide target DNA sequence within a genetic database consisting of up to 3,022 nucleotides. A conserved functional domain of the Cas9-like nucleotide sequence found in Brazilian biomes was used as the target sequence. Notably, this quantum algorithm permits a mismatch rate of up to 30% during the sequence comparison process. This enables flexible and rapid analysis in situations where sequence variations are expected, such as homologous gene analysis or evolutionary studies. Furthermore, based on these search results, the team succeeded in constructing a synthetic structure called a 'Quantum Biological Block (BioBloQu)' inside minimal cells (JCVI-syn3.0). The researchers stated that this algorithm "constitutes a unique starting point for developing a more sophisticated model for the manipulation of data". They also predicted that "the integration of quantum computing with artificial intelligence represents an attractive avenue... By optimizing genetic algorithms and facilitating real-time data analyses, quantum computing can revolutionize trait discovery processes in agriculture and biotechnology". This achievement is evaluated as an important example demonstrating how quantum computing can contribute to next-generation synthetic biology technologies that analyze large-scale genetic big data and design genomes from the bottom up.
∙ Quanta Magazine analyzes the principles of macroscopic world formation through quantum decoherence and quantum Darwinism. ∙ 'Einselection' fixes specific quantum states… similar to how life preserves information. ∙ Integrating quantum biology from physical and philosophical perspectives, redefining the fundamental principles of life's information processing. [Quantum Biology Society] An in-depth analysis has been proposed on how the bizarre phenomena of quantum mechanics transform into the solid macroscopic reality we observe, and what connection this process has with the evolution of life. Recently, the science media outlet Quanta Magazine reported through a contribution by renowned science writer Philip Ball that the theories of 'Quantum Darwinism' and 'Decoherence,' pioneered by physicist Wojciech Zurek, are the key to connecting biological systems with the macroscopic world. ■ The Reality of 'Survival of the Fittest' Created by 'Einselection' In the quantum realm, particles can exist in multiple states simultaneously (superposition), but in the macroscopic world we observe, they appear in only one definite state. According to Dr. Zurek's theory, this happens because quantum systems continuously interact with their surrounding environment, undergoing a process of 'decoherence' where information is dissipated. The core of this process is 'Einselection' (Environment-Induced Superselection). The environment does not accommodate all states; instead, it selects only the most stable and predictable states, known as 'pointer states,' and replicates them innumerably within the environment. Just as only the genetic information advantageous for survival is passed on and spreads in natural selection, the essence of 'Quantum Darwinism' is that quantum information also undergoes a 'survival of the fittest' process dictated by the environment. This ultimately forms an objective macroscopic reality that all of us can commonly perceive. ■ Life, a Product of Evolution that Anchors Quantum Information into Reality Philip Ball noted that these physical principles are strikingly similar to the way biological systems process information. He explains that the vital activities of living organisms—such as recognizing external stimuli, preserving genetic information, and controlling complex metabolic processes—are fundamentally the very processes of filtering meaningful information from quantum superpositions and anchoring them into the physical states of the real world. This report suggests that quantum biology is not merely a discipline that investigates microscopic reactions within cells. Rather, it is a grand unified theory explaining how life has utilized the universe's fundamental principles to process information and evolve. Built upon the theories of Dr. Zurek, a master of modern physics, this analysis presents a new philosophical and physical paradigm that views life as a cosmic entity where matter, information, and quantum mechanics are perfectly integrated.