Quantum Artificial Life Takes Its First Step on an IBM Quantum Computer
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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
•Jul 21, 2026•0 citations