Circuit Complexity Research Articles

Another Evidence to not Employ Customized Masked Hardware

As a well-studied countermeasure against side-channel analysis attacks, there is a general interest in applying masking to different cryptographic functions executed on different platforms. On the one hand, despite their high performance, masked hardware implementations are dedicated to specific algorithms, making them inflexible. On the other hand, applying masking on software involves serious challenges including significant overhead in terms of efficiency and difficulties to maintain theoretical security guarantees in practice. As a result, a line of research has been devoted to enable masked operations in flexible platforms (i.e., microprocessors) by including some masked modules in their hardware, hence a combination of flexibility and performance. In such scenarios, RISC-V is a natural choice as hardware can be adjusted to the extended instruction set. One such attempt presented at CHES 2021 is known as SCARV, which extends the Instruction Set Architecture (ISA) of a RISC-V core with a rich number of first-order masked operations on both Boolean and arithmetic masked operands. In this work, we conduct a comprehensive analysis of SCARV. Instead of relying on empirical measurements to demonstrate security, we utilize tool-assisted evaluations. Through these evaluations, we identified a couple of design flaws that lead to leakage in the masked implementations hosted by the corresponding processor. These flaws are primarily due to the lack of composability of cascaded components. While heuristic and ad-hoc design principles can result in secure, small, and efficient designs, they lack formal security proofs, which may lead to security flaws, like those we report here. Consequently, this work serves as a motivation for using composable masked modules and tool-assisted evaluations when constructing complex circuits.

Benchmarking of quantum fidelity kernels for Gaussian process regression

Abstract Quantum computing algorithms have been shown to produce performant quantum kernels for machine-learning classification problems. Here, we examine the performance of quantum kernels for regression problems of practical interest. For an unbiased benchmarking of quantum kernels, it is necessary to construct the most optimal functional form of the classical kernels and the most optimal quantum kernels for each given data set. We develop an algorithm that uses an analog of the Bayesian information criterion to optimize the sequence of quantum gates used to estimate quantum kernels for Gaussian process models. The algorithm increases the complexity of the quantum circuits incrementally, while improving the performance of the resulting kernels, and is shown to yield much higher model accuracy with fewer quantum gates than a fixed quantum circuit ansatz. We demonstrate that quantum kernels thus obtained can be used to build accurate models of global potential energy surfaces (PES) for polyatomic molecules. The average interpolation error of the six-dimensional PES obtained with a random distribution of 2000 energy points is 16 cm−1 for H3O+, 15 cm−1 for H2CO and 88 cm−1 for HNO2. We show that a compositional optimization of classical kernels for Gaussian process regression converges to the same errors. This indicates that quantum kernels can achieve the same, though not better, expressivity as classical kernels for regression problems.

Exploring the molecular and neuronal bases involved in central amygdala-dependent control of emotional behaviors

The central extended amygdala, including the central nucleus of the amygdala (CeA) and the lateral division of the bed nucleus of the stria terminalis (BNSTL), is a pivotal brain region involved in the threat processing responsible for emotional states such as fear and anxiety. These brain regions alter their circuit activities and exhibit necessary functions to adapt to environmental changes. When faced with excessive threats or stress, it is thought that these neural circuit functions are disrupted and cause various stress-related psychiatric disorders. The CeA and BNSTL were suggested to be the same nuclei separated during development because of their dense neural connections, and the similarities in cellular composition and connectivity patterns with other brain regions. On the other side, some recent studies suggested functional differences between these two regions in controlling emotional behaviors. However, functional segregation at the subnuclei level was insufficient since the two regions have complex circuit structures composed of multiple subnuclei. In this review, we introduce the similarities and differences between the CeA and BNSTL that have been clarified from our recent comparative studies of gene expression profiles and circuit functions at the subnuclei level. Additionally, we also discuss how it can contribute to understanding the molecular pathogenesis of neuropsychiatric disorders, including stress-related psychiatric disorders.

Foundation model of neural activity predicts response to new stimulus types and anatomy.

The complexity of neural circuits makes it challenging to decipher the brain's algorithms of intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brain's computational objectives and neural coding. However, these models struggle to generalize beyond their training distribution, limiting their utility. The emergence of foundation models, trained on vast datasets, has introduced a new AI paradigm with remarkable generalization capabilities. We collected large amounts of neural activity from visual cortices of multiple mice and trained a foundation model to accurately predict neuronal responses to arbitrary natural videos. This model generalized to new mice with minimal training and successfully predicted responses across various new stimulus domains, such as coherent motion and noise patterns. It could also be adapted to new tasks beyond neural prediction, accurately predicting anatomical cell types, dendritic features, and neuronal connectivity within the MICrONS functional connectomics dataset. Our work is a crucial step toward building foundation brain models. As neuroscience accumulates larger, multi-modal datasets, foundation models will uncover statistical regularities, enabling rapid adaptation to new tasks and accelerating research.

A Dual Constant Current Output Ports WPT System Based on Integrated Coil Decoupling: Analysis, Design, and Verification

With the high integration of power electronic devices, wireless power transfer (WPT) systems are required to have output characteristics of different specifications that are independent of the load. However, existing methods for realizing dual-output WPT systems have problems such as complex circuits, cumbersome control schemes, low system stability, insufficient system space utilization, and unnecessary cross-coupling. Therefore, in order to solve the above problems, this paper proposes a dual-receiver WPT system with dual constant current (CC) output based on an integrated decoupling coil. In this system, the DD coil is wound vertically in series with the solenoid coil and serves as the first receiving coil to achieve energy transmission in the system. While the solenoid coil is used in the transmitting coil and the second receiving coil, and the coils are perpendicular to each other to achieve natural decoupling. Furthermore, the receiving coils are integrated together on the receiving side ferrite plate. Therefore, there is no cross-coupling interference in the system, which simplifies the system design. Firstly, the natural decoupling characteristics of the magnetic coupler and the coil optimization method are analyzed in detail theoretically. Secondly, a detailed mathematical analysis is performed on the dual CC output characteristics with different specifications that are load-independent and have zero phase angle operation. Again, the zero voltage switching of the inverter can be achieved by changing the compensation component parameters through simulation verification. Finally, a prototype with a rated power of 283 W is constructed for validation purposes. The first receiver delivers a CC output of 3 A, while the second receiver provides a CC output of 4 A, with the DC–DC conversion efficiency reaching a peak of 90.2%. The experimental results confirm the accuracy of the theoretical analysis.

Multiplex Expression Cassette Assembly: A flexible and versatile method for building complex genetic circuits in conventional vectors.

The manipulation of multiple transcription units for simultaneous and coordinated expression is not only key to building complex genetic circuits to accomplish diverse functions in synthetic biology, but is also important in crop breeding for significantly improved productivity and overall performance. However, building constructs with multiple independent transcription units for fine-tuned and coordinated regulation is complicated and time-consuming. Here, we introduce the Multiplex Expression Cassette Assembly (MECA) method, which modifies canonical vectors compatible with Golden Gate Assembly, and then uses them to produce multi-cassette constructs. By embedding the junction syntax in primers that are used to amplify functional elements, MECA is able to make complex constructs using only one intermediate vector and one destination vector via two rounds of one-pot Golden Gate assembly reactions, without the need for dedicated vectors and a coherent library of standardized modules. As a proof-of-concept, we modified eukaryotic and prokaryotic expression vectors to generate constructs for transient expression of green fluorescent protein and β-glucuronidase in Nicotiana benthamiana, genome editing to block monoterpene metabolism in tomato glandular trichomes, production of betanin in tobacco and synthesis of β-carotene in Escherichia coli. Additionally, we engineered the stable production of thymol and carvacrol, bioactive compounds from Lamiaceae family plants, in glandular trichomes of tobacco. These results demonstrate that MECA is a flexible, efficient and versatile method for building complex genetic circuits, which will not only play a critical role in plant synthetic biology, but also facilitate improving agronomic traits and pyramiding traits for the development of next-generation elite crops.

STRAIGHT-IN: a platform for rapidly generating panels of genetically modified human pluripotent stem cell lines.

Targeted integration of large DNA cargoes (>10 kb) or genomic replacements in mammalian cells, such as human pluripotent stem cells (hPS cells), remains challenging. Here we describe a platform termed serine and tyrosine recombinase-assisted integration of genes for high-throughput investigation (STRAIGHT-IN) to circumvent this. First, a landing pad cassette is precisely inserted or used to replace specific genomic regions. The site-specific integrase Bxb1 then enables DNA constructs, including those >50 kb, to be integrated into the genome, while Cre recombinase excises auxiliary DNA sequences to prevent postintegrative silencing. Using a strategy whereby the positive selection marker is only expressed if the donor plasmid carrying the payload is correctly targeted, we can obtain 100% enrichment for cells containing the DNA payload. Procedures for expressing Cre efficiently also mean that a clonal isolation step is no longer essential to derive the required genetically modified hPS cells containing the integrated DNA, potentially reducing clonal variability. Furthermore, STRAIGHT-IN facilitates rapid and multiplexed generation of genetically matched hPS cells when multiple donor plasmids are delivered simultaneously. STRAIGHT-IN has various applications, which include integrating complex genetic circuits for synthetic biology, as well as creating panels of hPS cells lines containing, as necessary, hundreds of disease-linked variants for disease modeling and drug discovery. After establishing the hPS cell line containing the landing pad, the entire procedure, including donor plasmid synthesis, takes 1.5-3 months, depending on whether single or multiple DNA payloads are integrated. This protocol only requires the researcher to be skilled in molecular biology and standard cell culture techniques.

On the Consistency of Circuit Lower Bounds for Non-Deterministic Time

On the Consistency of Circuit Lower Bounds for Non-Deterministic Time

Homomorphic encryption of the k=2 Bernstein–Vazirani algorithm

Abstract We introduce a class of circuits that solve a particular case of the Bernstein–Vazirani recursive problem for second-level recursion. This class of circuits allows for the implementation of the oracle using a number of T-gates that grows linearly with the number of qubits in the problem. We find an application of this scheme to quantum homomorphic encryption (QHE), which is an important cryptographic technology useful for delegated quantum computing, allowing a remote server to perform quantum computations on encrypted quantum data, so that the server cannot know anything about the client’s data. Liang’s QHE schemes are suitable for circuits with a polynomial number of gates T / T † . Thus, the simplified circuits we have constructed can be evaluated homomorphically in an efficient manner.

Hardware circuit implementation of transmitter and receiver based on UART protocol

In today's information age, the amount of data as an important information carrier is growing at an explosive rate. The importance of its transmission rate, stability, accuracy and other properties is gradually becoming more and more important. UART as a communication protocol is widely used in embedded and IoT systems. It is simpler and more direct than SP2 and I2C, which can greatly simplify the complexity of digital circuits and become one of the key directions to improve the performance of data transmission. In this paper, a digital circuit based on the transmitter and receiver side of the UART protocol has been constructed using the hardware description language of Verilog HDL to implement the function of receiving and transmitting data based on a clock signal of 50 MHz and a baud rate of 115200 bps as well as the use of an RS232 asynchronous serial interface. The simulation was carried out using Quartus II.

Exponential qubit reduction in optimization for financial transaction settlement

We extend the qubit-efficient encoding presented in (Tan et al. in Quantum 5:454, 2021) and apply it to instances of the financial transaction settlement problem constructed from data provided by a regulated financial exchange. Our methods are directly applicable to any QUBO problem with linear inequality constraints. Our extension of previously proposed methods consists of a simplification in varying the number of qubits used to encode correlations as well as a new class of variational circuits which incorporate symmetries thereby reducing sampling overhead, improving numerical stability and recovering the expression of the cost objective as a Hermitian observable. We also propose optimality-preserving methods to reduce variance in real-world data and substitute continuous slack variables. We benchmark our methods against standard QAOA for problems consisting of 16 transactions and obtain competitive results. Our newly proposed variational ansatz performs best overall. We demonstrate tackling problems with 128 transactions on real quantum hardware, exceeding previous results bounded by NISQ hardware by almost two orders of magnitude.

Implementation of a fully integrated memristive Chua’s chaotic circuit with a voltage-controlled oscillator

In this paper, a fully integrated memristive Chua’s chaotic circuit based on the voltage-controlled oscillator is proposed. The memristor replaces the nonlinear diode, and the VCO (voltage-controlled oscillator) replaces the LC oscillator, eliminating the need for diodes, resistors, capacitors, and other complex circuit structures. The proposed chaotic circuit occupies a small chip area, only 0.0045 mm2, and achieves low power consumption of 2.8267 mW. The chaotic circuit is fabricated using the SMIC 180 nm CMOS process. The simulation results demonstrate that the VCO circuit can generate a frequency output ranging from 358 MHz to 1.1 GHz by varying Vc from 0 V to 2.8 V, with a power supply of 3.3 V. The value range of the Lyapunov index is 1.015 ∼1.03. The circuit offers advantages such as a stable power supply, low power consumption, and a small chip area.

A Gate-Level Power Estimation Approach with a Comprehensive Definition of Thresholds for Classification and Filtering of Inertial Glitch Pulses

Estimation of power consumption in digital circuits is performed at gate-level simulation. Its accuracy depends on the models of gate delays that capture the effects of spurious signal transitions, called “glitches”. Electronic Design Automation (EDA) software considers inertial gate delays and represses a glitch in the cell’s output if its width is below a threshold. Selecting threshold values for the inertial glitch classification and filtering is crucial for precise power estimations. In this direction, we explore the effectiveness of automatically adjusting such thresholds on a cell-specific basis according to the local cell’s information. We used a commercial industry-standard gate-level power estimation tool and a 32 nm CMOS standard cell library. Via power measurements in circuit simulations, we created customized lookup tables for each library cell employed in the benchmark circuits. We compared the proposed approach’s performance with other methods for glitch threshold definition. Our method demonstrated good power estimation accuracy while presenting the lowest mean absolute error among all the cells of the circuits under test and the smallest standard deviation. The latter suggests that the proposed method achieves better cell-specific accuracy, which is expected to allow for more precise circuit-level power estimations in complex circuits with a large number of combinational cells.

Experimentally Demonstrating Indefinite Causal Order Algorithms to Solve the Generalized Deutsch's Problem

AbstractDeutsch's algorithm is the first quantum algorithm to demonstrate an advantage over classical algorithms. Here, Deutsch's problem is generalized to functions and a quantum algorithm with an indefinite causal order is proposed to solve this problem. The algorithm not only reduces the number of queries to the black box by half compared to the classical algorithm, but also significantly decreases the complexity of the quantum circuit and the number of required quantum gates compared to the generalized Deutsch's algorithm. The algorithm is experimentally demonstrated in a stable Sagnac loop interferometer with a common path, which overcomes the obstacles of both phase instability and low fidelity of the Mach–Zehnder interferometer. The experimental results show both ultrahigh and robust success probabilities . This study opens a path toward solving practical problems with indefinite cause‐order quantum circuits.

BDD‐based optimized majority/minority gate using electro‐optic Mach‐Zehnder interferometer

AbstractIn this article, an optical majority/minority circuit has been designed using four electro‐optic Mach‐Zehnder interferometers. The binary decision diagram (BDD) is used to optimize the Boolean logical expression. In this design we get two outputs, one performs majority logic and the other performs minority logic simultaneously. Numerical simulation has been done with the obtained data from the beam propagation method. Pseudo‐eye diagram is also plotted to find amplitude modulation (AM) and extinction ratio (ER). AM and ER are found nearly 0.4 and 13 dB, respectively. A new parameter, the optical circuit complexity factor (OCC) factor has been calculated and from the result, it has been shown that the proposed design is more optimized than other majority/minority gate designs so far.

Exact pretransition effects in kinetically constrained circuits: Dynamical fluctuations in the Floquet-East model.

We study the dynamics of a classical circuit corresponding to a discrete-time version of the kinetically constrained East model. We show that this classical "Floquet-East" model displays pre-transition behavior which is a dynamical equivalent of the hydrophobic effect in water. For the deterministic version of the model, we prove exactly (i) a change in scaling with size in the probability of inactive space-time regions (akin to the "energy-entropy" crossover of the solvation free energy in water), (ii) a first-order phase transition in the dynamical large deviations, (iii) the existence of the optimal geometry for local phase separation to accommodate space-time solutes, and (iv) a dynamical analog of "hydrophobic collapse."

A modular toolkit for environmental Rhodococcus, Gordonia, and Nocardia enables complex metabolic manipulation.

Soil-dwelling Actinomycetes are a diverse and ubiquitous component of the global microbiome but largely lack genetic tools comparable to those available in model species such as Escherichia coli or Pseudomonas putida, posing a fundamental barrier to their characterization and utilization as hosts for biotechnology. To address this, we have developed a modular plasmid assembly framework, along with a series of genetic control elements for the previously genetically intractable Gram-positive environmental isolate Rhodococcus ruber C208, and demonstrate conserved functionality in 11 additional environmental isolates of Rhodococcus, Nocardia, and Gordonia. This toolkit encompasses five Mycobacteriale origins of replication, five broad-host-range antibiotic resistance markers, transcriptional and translational control elements, fluorescent reporters, a tetracycline-inducible system, and a counter-selectable marker. We use this toolkit to interrogate the carotenoid biosynthesis pathway in Rhodococcus erythropolis N9T-4, a weakly carotenogenic environmental isolate and engineer higher pathway flux toward the keto-carotenoid canthaxanthin. This work establishes several new genetic tools for environmental Mycobacteriales and provides a synthetic biology framework to support the design of complex genetic circuits in these species.IMPORTANCESoil-dwelling Actinomycetes, particularly the Mycobacteriales, include both diverse new hosts for sustainable biomanufacturing and emerging opportunistic pathogens. Rhodococcus, Gordonia, and Nocardia are three abundant genera with particularly flexible metabolisms and untapped potential for natural product discovery. Among these, Rhodococcus ruber C208 was shown to degrade polyethylene; Gordonia paraffinivorans can assimilate carbon from solid hydrocarbons; and Nocardia neocaledoniensis (and many other Nocardia spp.) possesses dual isoprenoid biosynthesis pathways. Many species accumulate high levels of carotenoid pigments, indicative of highly active isoprenoid biosynthesis pathways which may be harnessed for fermentation of terpenes and other commodity isoprenoids. Modular genetic toolkits have proven valuable for both fundamental and applied research in model organisms, but such tools are lacking for most Actinomycetes. Our suite of genetic tools and DNA assembly framework were developed for broad functionality and to facilitate rapid prototyping of genetic constructs in these organisms.

Study of Soft Errors in Spiking Neural Network Hardware

The problem of soft errors in the hardware implementation of Spiking Neural Networks (SNN) has always been a challenge. SNNs, unlike traditional deep learning networks, simulate the temporal dynamic behavior of biological neurons and emit spikes when a specific threshold is reached. In recent years, the hardware implementation of SNNs has shown great potential in performing efficient and low-power tasks, but as technology nodes shrink and integrated circuit complexity increases, soft errors become a key challenge. To this end, we propose a novel approach based on input and weight analysis, through specific algorithms at the hardware level, to significantly reduce the probability of soft errors affecting the results. In terms of training accuracy, our method maintains a high accuracy under various voltage fluctuation conditions, demonstrating its superior robustness.

CNTFET-Based Single-Ended Fractional Order Colpitts Oscillator: Design, Simulation and Comparative Analysis

In this paper, we design and simulate a Single-Ended Colpitts Oscillator (CO) in integer and fractional order domains. The oscillators are realized in 32[Formula: see text]nm node conventional MOSFET and carbon nanotube field effect transistor (CNTFET) technologies. Therefore, four COs have been designed, simulated and rigorously compared. These include integer order conventional MOSFET-based CO, fractional order MOSFET-based CO, CNTFET-based integer order CO and CNTFET-based fractional order CO, all based on 32-nm technology nodes. The fractional order approach has been used as it results in better control over the phase and frequency of the oscillator. Herein, fractional order capacitors of various orders, used in realizing the fractional order COs, are realized and their frequency responses are studied. This is being done to ensure whether the designed pseudo-capacitances have fractional behavior or not in the desired frequency and phase spectrum. It has been observed that the variation of fractional order [Formula: see text] from 0.4 to 0.81 has resulted in a slight reduction of oscillation frequency from 1.68[Formula: see text]GHz ([Formula: see text]) to 1.351[Formula: see text]GHz ([Formula: see text]) keeping the pseudo-capacitance same at 0.3[Formula: see text]nF in MOS-based topology. Since the fractional order realization increases the circuit complexity and power consumption, therefore, CNTFET-based integer order as well as fractional order COs have been designed. The CNTFET-based fractional order CO retains the advantages of the fractional order domain as well as the power efficiency of CNTFETs. Further, it has been observed that integrating fractional-order capacitor (FOC) with the CNTFET CO results in a much larger constant phase zone (CPZ), an important performance measuring parameter. A rigorous comparative analysis of the four COs designed in this work has been performed.

Tractable Circuits in Database Theory

This work reviews how database theory uses tractable circuit classes from knowledge compilation. We present relevant query evaluation tasks, and notions of tractable circuits. We then show how these tractable circuits can be used to address database tasks. We first focus on Boolean provenance and its applications for aggregation tasks, in particular probabilistic query evaluation. We study these for Monadic Second Order (MSO) queries on trees, and for safe Conjunctive Queries (CQs) and Union of Conjunctive Queries (UCQs). We also study circuit representations of query answers, and their applications to enumeration tasks: both in the Boolean setting (for MSO) and the multivalued setting (for CQs and UCQs).