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1. Engineering wetware and software for the predictive design of compressed genetic circuits for higher-state decision-making

   https://doi.org/10.1038/s41467-025-64457-0  

   Huang, Brian D; Yu, Yongjoon; Lee, Junghwan; Repasky, Matthew W; Xie, Yao; Realff, Matthew J; Wilson, Corey J (December 2025, Nature Communications)

   Andrews, Fraser (Ed.)

   Synthetic genetic circuits enable the reprogramming of cells and has advanced the study and application of biology with greater precision. However, quantitative circuit design is hampered by the limited modularity of biological parts. Moreover, as circuit complexity increases this imposes a greater metabolic burden on chassis cells limiting circuit design capacity. Here we present a generalizable technology composed of wetware and software to enable the quantitative design of highly compressed genetic circuits for higher-state decision-making. Wetware is composed of a new set of synthetic transcription factors facilitating the full development of compressed 3-input Boolean logic. Complementary software enables the design of compressed higher-state circuits, paired with a modeling workflow for the design of prescribed performance setpoints. On average the resulting multi-state compressed circuits were ~5-times smaller than canonical inverter-based genetic circuits. Our quantitative predictions had an average error below 1.4-fold validated via >50 test cases. Additionally, we applied said technology toward the predictive design of recombinase-based memory, and flux through a metabolic pathway. 

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2. Architectural mechanisms of a universal fault-tolerant quantum computer

   Bluvstein, Dolev; Geim, Alexandra_A; Li, Sophie_H; Evered, Simon_J; Bonilla_Ataides, J_Pablo; Baranes, Gefen; Gu, Andi; Manovitz, Tom; Xu, Muqing; Kalinowski, Marcin; et al (June 2025, arXivorg)

   Quantum error correction (QEC) is believed to be essential for the realization of large-scale quantum computers. However, due to the complexity of operating on the encoded `logical' qubits, understanding the physical principles for building fault-tolerant quantum devices and combining them into efficient architectures is an outstanding scientific challenge. Here we utilize reconfigurable arrays of up to 448 neutral atoms to implement all key elements of a universal, fault-tolerant quantum processing architecture and experimentally explore their underlying working mechanisms. We first employ surface codes to study how repeated QEC suppresses errors, demonstrating 2.14(13)x below-threshold performance in a four-round characterization circuit by leveraging atom loss detection and machine learning decoding. We then investigate logical entanglement using transversal gates and lattice surgery, and extend it to universal logic through transversal teleportation with 3D [[15,1,3]] codes, enabling arbitrary-angle synthesis with logarithmic overhead. Finally, we develop mid-circuit qubit re-use, increasing experimental cycle rates by two orders of magnitude and enabling deep-circuit protocols with dozens of logical qubits and hundreds of logical teleportations with [[7,1,3]] and high-rate [[16,6,4]] codes while maintaining constant internal entropy. Our experiments reveal key principles for efficient architecture design, involving the interplay between quantum logic and entropy removal, judiciously using physical entanglement in logic gates and magic state generation, and leveraging teleportations for universality and physical qubit reset. These results establish foundations for scalable, universal error-corrected processing and its practical implementation with neutral atom systems. 

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3. Quantum Circuit Synthesis Using Fuzzy-Logic-Assisted Genetic Algorithms

   https://doi.org/10.3390/a18040178  

   Islam, Ishraq; Jha, Vinayak; Thomas, Sneha; Egan, Kieran F; Nobel, Alvir; Kim, Serom; Chaudhary, Manu; Ogundele, Sunday; Kneidel, Dylan; Phillips, Ben; et al (April 2025, Algorithms)

   Quantum algorithms will likely play a key role in future high-performance-computing (HPC) environments. These algorithms are typically expressed as quantum circuits composed of arbitrary gates or as unitary matrices. Executing these on physical devices, however, requires translation to device-compatible circuits, in a process called quantum compilation or circuit synthesis, since these devices support a limited number of native gates. Moreover, these devices typically have specific qubit topologies, which constrain how and where gates can be applied. Consequently, logical qubits in input circuits and unitaries may need to be mapped to and routed between physical qubits. Furthermore, current Noisy Intermediate-Scale Quantum (NISQ) devices present additional constraints. They are vulnerable to errors during gate application and their short decoherence times lead to qubits rapidly succumbing to accumulated noise and possibly corrupting computations. Therefore, circuits synthesized for NISQ devices need to minimize gates and execution times. The problem of synthesizing device-compatible circuits, while optimizing for low gate count and short execution times, can be shown to be computationally intractable using analytical methods. Therefore, interest has grown towards heuristics-based synthesis techniques, which are able to produce approximations of the desired algorithm, while optimizing depth and gate-count. In this work, we investigate using genetic algorithms (GA)—a proven gradient-free optimization technique based on natural selection—for circuit synthesis. In particular, we formulate the quantum synthesis problem as a multi-objective optimization (MOO) problem, with the objectives of minimizing the approximation error, number of multi-qubit gates, and circuit depth. We also employ fuzzy logic for runtime parameter adaptation of GA to enhance search efficiency and solution quality in our proposed method. 

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4. Logical quantum processor based on reconfigurable atom arrays

   https://doi.org/10.1038/s41586-023-06927-3  

   Bluvstein, Dolev; Evered, Simon J.; Geim, Alexandra A.; Li, Sophie H.; Zhou, Hengyun; Manovitz, Tom; Ebadi, Sepehr; Cain, Madelyn; Kalinowski, Marcin; Hangleiter, Dominik; et al (December 2023, Nature)

   Abstract Suppressing errors is the central challenge for useful quantum computing¹, requiring quantum error correction (QEC)^2–6for large-scale processing. However, the overhead in the realization of error-corrected ‘logical’ qubits, in which information is encoded across many physical qubits for redundancy^2–4, poses substantial challenges to large-scale logical quantum computing. Here we report the realization of a programmable quantum processor based on encoded logical qubits operating with up to 280 physical qubits. Using logical-level control and a zoned architecture in reconfigurable neutral-atom arrays⁷, our system combines high two-qubit gate fidelities⁸, arbitrary connectivity^7,9, as well as fully programmable single-qubit rotations and mid-circuit readout^10–15. Operating this logical processor with various types of encoding, we demonstrate improvement of a two-qubit logic gate by scaling surface-code⁶distance fromd = 3 tod = 7, preparation of colour-code qubits with break-even fidelities⁵, fault-tolerant creation of logical Greenberger–Horne–Zeilinger (GHZ) states and feedforward entanglement teleportation, as well as operation of 40 colour-code qubits. Finally, using 3D [[8,3,2]] code blocks^16,17, we realize computationally complex sampling circuits¹⁸with up to 48 logical qubits entangled with hypercube connectivity¹⁹with 228 logical two-qubit gates and 48 logical CCZ gates²⁰. We find that this logical encoding substantially improves algorithmic performance with error detection, outperforming physical-qubit fidelities at both cross-entropy benchmarking and quantum simulations of fast scrambling^21,22. These results herald the advent of early error-corrected quantum computation and chart a path towards large-scale logical processors. 

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5. Revolutionizing Computations: Quantum Circuit Analogues with Nonlinear Acoustic Waves

   Hasan, M Arif; Deymier, Pierre; Runge, Keith; Levine, Josh (March 2024, The American Institute of Physics, publisher, Bulletin of the American Physical Society)

   Quantum computing utilizes superposition and entanglement to surpass classical computer capabilities. Central to this are qubits and their use to realize parallel quantum algorithms through circuits of simple one or two qubit gates. Controlling and measuring quantum systems is challenging. Here, we introduce a paradigm utilizing logical phi-bits, classical analogues of qubits using nonlinear acoustic waves, supported by an externally driven acoustic metastructure. These phi-bits bridge a low-dimensional linearly scaling physical space to a high-dimensional exponentially scaling Hilbert space in which parallel processing of information can be realized in the form of unitary operations. Here, we show the implementation of a nontrivial three-phi-bit unitary operation analogous to a quantum circuit but achieved via a single action on the metastructure, whereby the qubit-based equivalent requires sequences of qubit gates. A phi-bit-based approach might offer advantages over quantum systems, especially in tasks requiring large complex unitary operations. This breakthrough hints at a fascinating intersection of classical and quantum worlds, potentially redefining computational paradigms by harnessing nonlinear classical mechanical systems in quantum-analogous manners, blending the best of both domains. 

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