Information Processing In Circuits Research Articles

Exploring multi-qubit analogue operations through acoustic wave dynamics

Quantum computing harnesses quantum phenomena like superposition and entanglement to surpass classical computers, showing promise across various fields. Current techniques utilize qubits in quantum circuits for parallel information processing, though managing and measuring these systems poses significant challenges. We propose a novel approach to simplify executing complex quantum algorithms without relying on multiple quantum gate operations. Our method introduces logical phi-bits—classical counterparts to qubits, using nonlinear acoustic waves in an externally driven acoustic metastructure. We demonstrate that complex multi-phi-bit unitary operations, akin to those in quantum circuits, can be conducted through a single action on this metastructure. This method starkly contrasts traditional quantum computing, which requires decomposed sequences of qubit gates for equivalent operations. The phi-bit system simplifies processes that are typically complex in quantum mechanics, potentially enhancing robustness and ease of implementation. Our results indicate that phi-bits could expand computational models by merging classical wave dynamics with quantum computational principles, thereby widening the potential of computational technologies. This research advances quantum-analogue computation and introduces new prospects for utilizing wave physics in information processing, thereby challenging and expanding existing paradigms in both classical and quantum computing. [Funding: NSF grant 2204382, 2204400, and 2242925.]

Nature of Long-Lived Moiré Interlayer Excitons in Electrically Tunable MoS2/MoSe2 Heterobilayers.

Interlayer excitons in transition-metal dichalcogenide heterobilayers combine high binding energy and valley-contrasting physics with a long optical lifetime and strong dipolar character. Their permanent electric dipole enables electric-field control of the emission energy, lifetime, and location. Device material and geometry impact the nature of the interlayer excitons via their real- and momentum-space configurations. Here, we show that interlayer excitons in MoS2/MoSe2 heterobilayers are formed by charge carriers residing at the Brillouin zone edges, with negligible interlayer hybridization. We find that the moiré superlattice leads to the reversal of the valley-dependent optical selection rules, yielding a positively valued g-factor and cross-polarized photoluminescence. Time-resolved photoluminescence measurements reveal that the interlayer exciton population retains the optically induced valley polarization throughout its microsecond-long lifetime. The combination of a long optical lifetime and valley polarization retention makes MoS2/MoSe2 heterobilayers a promising platform for studying fundamental bosonic interactions and developing excitonic circuits for optical information processing.

Broadband and fabrication-tolerant 3-dB couplers with topological valley edge modes

3-dB couplers, which are commonly used in photonic integrated circuits for on-chip information processing, precision measurement, and quantum computing, face challenges in achieving robust performance due to their limited 3-dB bandwidths and sensitivity to fabrication errors. To address this, we introduce topological physics to nanophotonics, developing a framework for topological 3-dB couplers. These couplers exhibit broad working wavelength range and robustness against fabrication dimensional errors. By leveraging valley-Hall topology and mirror symmetry, the photonic-crystal-slab couplers achieve ideal 3-dB splitting characterized by a wavelength-insensitive scattering matrix. Tolerance analysis confirms the superiority on broad bandwidth of 48 nm and robust splitting against dimensional errors of 20 nm. We further propose a topological interferometer for on-chip distance measurement, which also exhibits robustness against dimensional errors. This extension of topological principles to the fields of interferometers, may open up new possibilities for constructing robust wavelength division multiplexing, temperature-drift-insensitive sensing, and optical coherence tomography applications.

Memristive switching of nanofluidic diodes by ionic concentration gradients

We demonstrate that nanofluidic diodes exhibit a memristive behavior that can be controlled not only by the amplitude and frequency of the driving oscillatory signal but also by changing the relative orientations of the externally imposed ionic concentration difference with respect to the pore charge density gradient. Because ionic concentration differences, memristive properties, and nanofluidic pores are of broad interest to electrochemical technology and membrane bioelectrochemistry, this study can be a useful contribution to the field. In our case, the memristor is a polymer membrane with current rectifying conical nanopores. The electrical interaction between the mobile ions in the aqueous solution and the pore surface charges leads to rich physico-chemical phenomena, including memory effects and the neuromorphic-like potentiation of the membrane conductance following voltage pulses (spikes). The multipore membrane can be used in the design of electrochemical circuits for signal conversion and information processing in iontronic hybrid devices.

The Goldilocks principle of learning unitaries by interlacing fixed operators with programmable phase shifters on a photonic chip

Programmable photonic integrated circuits represent an emerging technology that amalgamates photonics and electronics, paving the way for light-based information processing at high speeds and low power consumption. Programmable photonics provides a flexible platform that can be reconfigured to perform multiple tasks, thereby holding great promise for revolutionizing future optical networks and quantum computing systems. Over the past decade, there has been constant progress in developing several different architectures for realizing programmable photonic circuits that allow for realizing arbitrary discrete unitary operations with light. Here, we systematically investigate a general family of photonic circuits for realizing arbitrary unitaries based on a simple architecture that interlaces a fixed intervening layer with programmable phase shifter layers. We introduce a criterion for the intervening operator that guarantees the universality of this architecture for representing arbitrary N×N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N \ imes N$$\\end{document} unitary operators with N+1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N+1$$\\end{document} phase layers. We explore this criterion for different photonic components, including photonic waveguide lattices and meshes of directional couplers, which allows the identification of several families of photonic components that can serve as the intervening layers in the interlacing architecture. Our findings pave the way for efficiently designing and realizing novel families of programmable photonic integrated circuits for multipurpose analog information processing.

Modeling of memory effects in nanofluidic diodes

Nanofluidic diodes and ionic solutions find application in electrochemical circuits for information processing, controlled release, and signal conversion in hybrid devices. Here, we describe a physical model that accounts for the memory effects observed in conical nanopores in terms of the driving signal and ionic solution characteristics. The concepts invoked describe the device operation on the basis of the electrical interaction between the pore surface charges and the nanoconfined ionic solution. The physical insights provided can explain the experimental dependence of the nanofluidic tunability on the amplitude and frequency of the driving signal, the ionic concentration, and the solution pH. The model should also be useful for the design of electrochemical circuits based on ionic conduction in asymmetric memristors.

A prefrontal-thalamic circuit encodes social information for social recognition.

Social recognition encompasses encoding social information and distinguishing unfamiliar from familiar individuals to form social relationships. Although the medial prefrontal cortex (mPFC) is known to play a role in social behavior, how identity information is processed and by which route it is communicated in the brain remains unclear. Here we report that a ventral midline thalamic area, nucleus reuniens (Re) that has reciprocal connections with the mPFC, is critical for social recognition in male mice. In vivo single-unit recordings and decoding analysis reveal that neural populations in both mPFC and Re represent different social stimuli, however, mPFC coding capacity is stronger. We demonstrate that chemogenetic inhibitions of Re impair the mPFC-Re neural synchronization and the mPFC social coding. Projection pathway-specific inhibitions by optogenetics reveal that the reciprocal connectivity between the mPFC and the Re is necessary for social recognition. These results reveal an mPFC-thalamic circuit for social information processing.

Design of a Biohybrid Materials Circuit with Binary Decoder Functionality.

Synthetic biology applies concepts from electrical engineering and information processing to endow cells with computational functionality. Transferring the underlying molecular components into materials and wiring them according to topologies inspired by electronic circuit boards has yielded materials systems that perform selected computational operations. However, the limited functionality of available building blocks is restricting the implementation of advanced information-processing circuits into materials. Here, a set of protease-based biohybrid modules the bioactivity of which can either be induced or inhibited is engineered. Guided by a quantitative mathematical model and following a design-build-test-learn (DBTL) cycle, the modules are wired according to circuit topologies inspired by electronic signal decoders, a fundamental motif in information processing. A 2-input/4-output binary decoder for the detection of two small molecules in a material framework that can perform regulated outputs in form of distinct protease activities is designed. The here demonstrated smart material system is strongly modular and can be used for biomolecular information processing for example in advanced biosensing or drug delivery applications.

Biomimetic Random Pulse Computation or Why Do Humans Play Basketball Better than Robots?

In this work, we compare the basketball scoring performance of two imaginary (simulated) mechanical robots in conditions of erroneous information-processing circuits: Machine, whose moves are controlled by a conventional digital computer and Man, controlled by a random pulse computer composed of biologically-inspired circuits which execute basic arithmetic operations. This is the first comparative study of robustness of the digital and the random pulse computing paradigms, with respect to the error rate of the information-processing circuits (perr), for a mechanical robot. In spite of the fact that Man's computer consists of only about 100 logic gates while Machine's requires about 3500 gates, Man achieves a significantly higher scoring probability for perr in the range from 0.01% all the way to 10%, while at lower perr, both converge to the perfect score. Furthermore, Man's hits make up a smooth Gaussian distribution with a vanishing probability of making large misses even at the highest perr, while Machine is prone to spectacular misses already at perr as low as 1 part-per-million. These findings indicate that the biologically inspired computation requires less hardware for the same task, and ensures higher robustness and better behaving operation than digital computation, which are characteristics of importance for the survivability of living beings.

Effects of multisession cathodal transcranial direct current stimulation with cognitive training on sociocognitive functioning and brain dynamics in autism: A double-blind, sham-controlled, randomized EEG study

BackgroundFew treatment options are available for targeting core symptoms of autism spectrum disorder (ASD). The development of treatments that target common neural circuit dysfunctions caused by known genetic defects, namely, disruption of the excitation/inhibition (E/I) balance, is promising. Transcranial direct current stimulation (tDCS) is capable of modulating the E/I balance in healthy individuals, yet its clinical and neurobiological effects in ASD remain elusive. ObjectiveThis double-blind, randomized, sham-controlled trial investigated the effects of multisession cathodal prefrontal tDCS coupled with online cognitive remediation on social functioning, information processing efficiency and the E/I balance in ASD patients aged 14–21 years. MethodsSixty individuals were randomly assigned to receive either active or sham tDCS (10 sessions in total, 20 min/session, stimulation intensity: 1.5 mA, cathode: F3, anode: Fp2, size of electrodes: 25 cm2) combined with 20 min of online cognitive remediation. Social functioning, information processing efficiency during cognitive tasks, and theta- and gamma-band E/I balance were measured one day before and after the treatment. ResultsCompared to sham tDCS, active cathodal tDCS was effective in enhancing overall social functioning [F(1, 58) = 6.79, p = .012, ηp2 = 0.105, 90% CI: (0.013, 0.234)] and information processing efficiency during cognitive tasks [F(1, 58) = 10.07, p = .002, ηp2 = 0.148, 90% CI: (0.034, 0.284)] in these individuals. Electroencephalography data showed that this cathodal tDCS protocol was effective in reducing the theta-band E/I ratio of the cortical midline structures [F(1, 58) = 4.65, p = .035, ηp2 = 0.074, 90% CI: (0.010, 0.150)] and that this reduction significantly predicted information processing efficiency enhancement (b = −2.546, 95% BCa CI: [-4.979, −0.113], p = .041). ConclusionOur results support the use of multisession cathodal tDCS over the left dorsolateral prefrontal cortex combined with online cognitive remediation for reducing the elevated theta-band E/I ratio in sociocognitive information processing circuits in ASD patients, resulting in more adaptive regulation of global brain dynamics that is associated with enhanced information processing efficiency after the intervention.

Synchronization in STDP-driven memristive neural networks with time-varying topology

Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by spike-timing-dependent plasticity (STDP) and temporal networks subject to homeostatic structural plasticity (HSP) rules remain unclear. Here, we bridge this gap by determining the configurations required to achieve high and stable degrees of complete synchronization (CS) and phase synchronization (PS) in time-varying small-world and random neural networks driven by STDP and HSP. In particular, we found that decreasing P (which enhances the strengthening effect of STDP on the average synaptic weight) and increasing F (which speeds up the swapping rate of synapses between neurons) always lead to higher and more stable degrees of CS and PS in small-world and random networks, provided that the network parameters such as the synaptic time delay tau _c, the average degree langle k rangle, and the rewiring probability beta have some appropriate values. When tau _c, langle k rangle, and beta are not fixed at these appropriate values, the degree and stability of CS and PS may increase or decrease when F increases, depending on the network topology. It is also found that the time delay tau _c can induce intermittent CS and PS whose occurrence is independent F. Our results could have applications in designing neuromorphic circuits for optimal information processing and transmission via synchronization phenomena.

Light-Triggered Reversible Tuning of Second-Harmonic Generation in a Photoactive Plasmonic Molecular Nanocavity.

The ultrasmall mode volume and ultralarge local field enhancement of compact plasmonic nanocavities have been widely explored to amplify a variety of optical phenomena at the nanoscale. Other than passively generating near-field enhancements, dynamic tuning of their intensity and associated nonlinear optical processes such as second-harmonic generation (SHG) play vital roles in the field of active nanophotonics. Here we apply a host-guest molecular complex to construct a photoswitchable molecule-sandwiched metallic particle-on-film nanocavity (MPoFN) and demonstrate both light-controlled linear and nonlinear optical tuning. Under alternating illumination of ultraviolet (UV) and visible light, the photoactive plasmonic molecular nanocavity shows reversible switching of both surface-enhanced Raman scattering (SERS) and plasmon resonance. Surprisingly, we observe more significant modulation of SHG from this photoactive MPoFN, which can be explained qualitatively by the quantum conductivity theory (QCT). Our study could pave the way for developing miniaturized integrated optical circuits for ultrafast all-optical information processing and communication.

Pilot Study on the Visualization of Latent Fingerprints and Naked Eye Detection of Hg2+ and Zn2+ Ions in Aqueous Media Using Ninhydrin-Based Thiosemicarbazone.

Here, we described a cheap and effective chemosensor (NHPyTSC) that can distinguish Hg2+ and Zn2+ ions from other metal ions and evaluated this phenomenon using several spectroscopy techniques. With the addition of mercury and zinc ions, the proposed chemosensor in particular showed noticeable changes in color and absorption spectra. Additionally, by including EDTA in the NHPyTSC-Hg2+ and NHPyTSC-Zn2+ solutions, colorimetry readings can be reversed. We developed a molecular-scale sequential information processing circuit and presented the "writing-reading-erasing-reading" and "multiwrite" behaviors in the form of binary logic based on the great reversibility of this process. Moreover, by sequentially adding Hg2+, Zn2+, and EDTA, NHPyTSC imitates a molecular keypad lock and molecular logic gates. Density functional theory (DFT) investigations provided more evidence of the Hg2+ and Zn2+ ions' ability to attach to NHPyTSC. The most interesting part of this work is that a study on the latent fingerprint detection of the powder compound revealed that NHPyTSC exhibits good adherence and finger ridge features without background stains. When compared to black and white fingerprint powders, it is discovered that the NHPyTSC powder produces results that are remarkably clear on the majority of surfaces. This demonstrated their potential for real-world use, particularly in the area of criminal investigations.

Class Brain Coprocessor based on Neuromorphic Circuit for Efficient Non-Formalization and Unstructured Information Processing

Class brain coprocessor is a type of coprocessor based on neuromorphic circuits that includes a memory module for storing training characteristics information, a processing module based on a hierarchical structure, and an encoder and decoder for input and output. This research proposes a memory module with a training characteristics storehouse and/or configurable training characteristics storehouse, and a processing module with a solidification functional network module and/or configurable functionality mixed-media network modules, which enhances the extended capability of the coprocessor. The proposed coprocessor employs distributed storage and concurrent collaborative processing, making it particularly suitable for handling non-formalization problems and unstructured information, as well as form problems and structured messages. The results show that this coprocessor significantly accelerates the speed of computers in processing class brain,informationificial intelligence, and reduces energy consumption while improving fault-tolerant ability, reducing programming complexity, and improving computing power.

Design of single-electron information-processing circuit modeled on Boids algorithm of fish shoals

We designed an analog single-electron (SE) information-processing circuit that mimics the behavior of a fish shoal. Although SE circuits are functional, there is not yet an optimum information-processing method established for them. To tackle this issue, we take inspiration from the behavior of fish shoals, where each fish determines its behavior by interacting with other fish, as in a multi-agent system. We demonstrated our SE circuit to effectively mimic one of the three rules of the Boids algorithm regarding fish shoal behavior through computer simulation. We believe our approach is a strong candidate for SE circuits having optimum information processing.

Building a pipeline to identify and engineer constitutive and repressible promoters.

To support the increasingly complex circuits needed for plant synthetic biology applications, additional constitutive promoters are essential. Reusing promoter parts can lead to difficulty in cloning, increased heterogeneity between transformants, transgene silencing and trait instability. We have developed a pipeline to identify genes that have stable expression across a wide range of Arabidopsis tissues at different developmental stages and have identified a number of promoters that are well expressed in both transient (Nicotiana benthamiana) and stable (Arabidopsis) transformation assays. We have also introduced two genome-orthogonal gRNA target sites in a subset of the screened promoters, converting them into NOR logic gates. The work here establishes a pipeline to screen for additional constitutive promoters and can form the basis of constructing more complex information processing circuits in the future.

Design of comb-shaped single-electron slime mold circuit and its application to traveling salesman problem

We propose a single-electron (SE) information processing circuit that mimics the behavior of slime mold. While SE circuits have advantages such as parallel processing and low power consumption, a suitable information processing method has not yet been established for them. Thus, we focus on the behavior of slime mold to develop a suitable information processing method. Reportedly, slime molds can solve the traveling salesman problem (TSP) if their behaviors (i.e. stretching and shrinking) are harnessed. In a simulation results, our information processing method for SE circuits mimics a series of slime mold behaviors to derive the optimal solutions for the TSP.

Computational capacity of LRC , memristive, and hybrid reservoirs

Reservoir computing is a machine learning paradigm that uses a high-dimensional dynamical system, or reservoir, to approximate and predict time series data. The scale, speed, and power usage of reservoir computers could be enhanced by constructing reservoirs out of electronic circuits, and several experimental studies have demonstrated promise in this direction. However, designing quality reservoirs requires a precise understanding of how such circuits process and store information. We analyze the feasibility and optimal design of electronic reservoirs that include both linear elements (resistors, inductors, and capacitors) and nonlinear memory elements called memristors. We provide analytic results regarding the feasibility of these reservoirs and give a systematic characterization of their computational properties by examining the types of input-output relationships that they can approximate. This allows us to design reservoirs with optimal properties. By introducing measures of the total linear and nonlinear computational capacities of the reservoir, we are able to design electronic circuits whose total computational capacity scales extensively with the system size. Our electronic reservoirs can match or exceed the performance of conventional "echo state network" reservoirs in a form that may be directly implemented in hardware.

Nanocavity-induced trion emission from atomically thin WSe2

Exciton is a bosonic quasiparticle consisting of a pair of electron and hole, with promising potentials for optoelectronic device applications, such as exciton transistors, photodetectors and light emitting devices. However, the charge-neutral nature of excitons renders them challenging to manipulate using electronics. Here we present the generation of trions, a form of charged excitons, together with enhanced exciton resonance in monolayer WSe2. The excitation of the trion quasiparticles is achieved by the hot carrier transport from the integrated gold plasmonic nanocavity, formed by embedding monolayer WSe2 between gold nanoparticles and a gold film. The nanocavity-induced negatively charged trions provide a promising route for the manipulation of excitons, essential for the construction of all-exciton information processing circuits.

An efficient 2-aminothiazolesalicylaldehyde fluorescent chemosensor for Fe2+ ion detection and a potential inhibitor of NUDT5 signaling hormone for breast cancer cell and molecular keypad lock application

A novel thiazole phenol conjugate, 2-aminothiazolesalicylaldehyde (receptor1) was designed and synthesized for the first time through a single step process via Schiff base condensation reaction. The formation of receptor1 was confirmed by FTIR, 13C NMR, and 1H NMR. The IR spectra confirmed the presence of the aldimine formation. It is further supported by the proton NMR, showing the disappearance of aldehyde peaks and the formation of a new imine peak. This is further corroborated by the 13C NMR. The receptor1 complexing with various metal ions were studied through fluorescence spectroscopy showed its selectivity toward Fe2+ ion following a reverse photoinduced electron transfer (PET) process compared to all other potentially competing ions. The receptor1 was applied as a sensor to sense Fe2+ ion in water samples. The detection limit for Fe2+ ion in drinking water was substantially lower (0.003 µM) than the EPA (environmental protection agency) recommendation (5.37 M). The capability of receptor1 in recovering Fe2+ ion in bore water, tap water, and drinking water was up to 99.5%. The receptor1 was also used as a chelating ligand (receptor1) in molecular docking and it was assessed as a potential inhibitor of NUDT5, a silence hormone signaling for breast cancer. The test compound (PDB: 5NWH) showed good affinity toward the target receptor1 with the binding energy of – 5.23 kcal mol−1. Furthermore, the receptor1 showed excellent reversibility property on adding EDTA solution. Due to the marvelous reversible property, a molecular-scale sequential information processing circuit is designed for the multi-task behavior such as ‘Writing-Reading-Erasing-Reading’ in the form of binary logic gate. The consecutive addition of Fe2+ ion and EDTA solution to receptor1 paves a way for the construction of INHIBIT logic gate. Additionally, the receptor1 showed the mimicking behavior of molecular keypad lock.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11696-022-02373-z.