In this critical review we review enzymatic systems which involve biocatalytic reactions utilized for information processing (biocomputing). Extensive ongoing research in biocomputing, mimicking Boolean logic gates has been motivated by potential applications in biotechnology and medicine. Furthermore, novel sensor concepts have been contemplated with multiple inputs processed biochemically before the final output is coupled to transducing “smart-material” electrodes and other systems. These applications have warranted recent emphasis on networking of biocomputing gates. First few-gate networks have been experimentally realized, including coupling, for instance, to signal-responsive electrodes for signal readout. In order to achieve scalable, stable network design and functioning, considerations of noise propagation and control have been initiated as a new research direction. Optimization of single enzyme-based gates for avoiding analog noise amplification has been explored, as were certain network-optimization concepts. We review and exemplify these developments, as well as offer an outlook for possible future research foci. The latter include design and uses of non-Boolean network elements, e.g., filters, as well as other developments motivated by potential novel sensor and biotechnology applications (136 references).

For a solvable pure-decoherence model, we confirm by an explicit model calculation that the decay of entanglement of two two-state systems (two qubits) is approximately governed by the product of the suppression factors describing decoherence of the subsystems, provided that they are subject to uncorrelated sources of quantum noise. This demonstrates an important physical property that separated open quantum systems can evolve quantum mechanically on time scales larger than the times for which they remain entangled.

Molecular weight distributions (MWD) have a substantial impact on a diverse set of polymer physical and rheological properties, from processability and stiffness to many aspects of block copolymer microphase behavior. The precise MWD compositions of these polymers can be modularly controlled through temporal initiation in anionic polymerizations by metered addition of a discrete initiating species. With the technique described in this work, we identify initiator addition profiles through theoretical modeling which can be used to prepare any desired arbitrary MWD. This kinetic model reproduces experimental MWDs with high fidelity. Our modeling strategy incorporates a detailed kinetic description of polymer initiation and propagation, including the association and dissociation equilibria of the living polymer chain ends. We simplify the kinetic model by incorporating the aggregation phenomena into an effective propagation rate constant k_p, allowing it to vary with the polymer chain length (i). Importantly, this model also yields the ability to predict MWDs at any arbitrary value of monomer conversion during the polymerization. Lastly, we simulate MWDs for a variety of new, yet unmeasured, initiator addition profiles, demonstrating the predictability of this approach.

A short-time approximation is developed for system-environmental bath mode interactions involving a general non-Hermitian system operator $\Lambda$ and its conjugate ${\Lambda }^{†}$ in order to evaluate the onset of decoherence at low temperatures in quantum systems interacting with the environment. The developed approach is complementary to Markovian approximations and appropriate for the evaluation of quantum computing schemes. An example of a spin system coupled to a bosonic heat bath via $\Lambda \propto {\sigma }_{-}$ is worked out in detail.