Circuit Complexity Research Articles

Performance study of variational quantum linear solver with an improved ansatz for reservoir flow equations

This paper studies the performance of the variational quantum linear solver (VQLS) with an improved ansatz for discretized reservoir flow equations for the first time. First, we introduce the two typical flow equations in reservoir simulation, namely, the diffusion equation for pressure and the convection-dominated Buckley–Leverett equation for water saturation, and their commonly used finite volume or finite difference-based discretized linear equations. Then, we propose an improved ansatz in VQLS to enhance the convergence and accuracy of VQLS and a strategy of adjusting grid order to reduce the complexity of the quantum circuit for preparing the quantum state corresponding to the coefficient vector of the discretized reservoir flow equations. Finally, we apply the modified VQLS to solve the discretized reservoir flow equations by employing the Xanadu's PennyLane open-source library. Four numerical examples are implemented, and the results show that VQLS can calculate reservoir flow equations with high accuracy, and the improved ansatz significantly outperforms the original one. Moreover, we study the effects of reservoir heterogeneity, the number of ansatz layers, the equation type, and the number of shots on the computational performance. Limited by the current computing capacity, the number of grids subject to the involved number of quantum bits in the implemented examples is small; we will further explore this quantum algorithm to practical examples that require a large number of quantum bits in the future.

Design and Implementation of a LoRa Technology - Based Smart Home Monitoring Circuit

This paper offers a detailed design and real-world execution of a complex electrical circuit for smart homes that employs LoRa technology to monitor significant environmental conditions and the operating state of home equipment. The circuit's novel design allows it to monitor power usage and the on/off state of home appliances, in addition to measuring temperature and humidity with extreme precision. With its reputation for long-range and low-power wireless communication, LoRa technology is used by the core microcontroller of the system, which also processes sensor data. This is why the system works particularly effectively in large residences where other wireless technologies would have trouble. The solution ensures consistent and dependable data transmission using LoRa, even in the face of the common architectural obstacles seen in residential environments. To facilitate data analysis and remote monitoring, an electrical circuit was made to be readily linked to a central hub for home automation. A comprehensive assessment procedure was used for implementation in different household environments to determine responsiveness, dependability, and user-centered design. The empirical findings demonstrate how well the circuit works to provide homes with practical advice on how to best regulate device use and optimize the interior temperature, which eventually improves comfort and energy efficiency. To achieve next-generation home automation systems, LoRa-based solutions are critical, and the article concludes by analyzing the consequences of this study on the future landscape of smart-house technologies.

Quantum Talagrand, KKL and Friedgut’s Theorems and the Learnability of Quantum Boolean Functions

We extend three related results from the analysis of influences of Boolean functions to the quantum setting, namely the KKL theorem, Friedgut’s Junta theorem and Talagrand’s variance inequality for geometric influences. Our results are derived by a joint use of recently studied hypercontractivity and gradient estimates. These generic tools also allow us to derive generalizations of these results in a general von Neumann algebraic setting beyond the case of the quantum hypercube, including examples in infinite dimensions relevant to quantum information theory such as continuous variables quantum systems. Finally, we comment on the implications of our results as regards to noncommutative extensions of isoperimetric type inequalities, quantum circuit complexity lower bounds and the learnability of quantum observables.

Classification of wafer map defect based on ResNeSt

With the increasing circuit complexity of chip design, wafers are prone to defects in the production process. Since different defects have their causes, post-analysis is important to wafer production. However, the sample size is not balanced, and the effect of classical residual networks is limited. This article uses a Split-Attention network (ResNeSt) with which feature maps will be input into k-base groups, each consisting of r groups. Thanks to the large receptive field, image features can be obtained better. We add channel attention and give higher weight to the effective feature channels to improve network performance. Compared with the classical residual network, the new network has an improvement of 43.06%, 32.73%, and 10.86% in handling Scratch, Near-full, and Local defects, respectively.

Construction of logic circuit with modular molecular switching strategy based on DNA strand displacement

SummaryAt present, many DNA logic circuits have been successfully constructed. However, advanced complex DNA computing tasks with simple structure, fast response, and modularization still remain a huge challenge. In this paper, molecular switch circuits (MSCs) are constructed based on DNA strand displacement to improve above problems. At first, molecular switch is constructed, which is the basic element for building logic circuits. Next, the functions of AND, OR, Fan‐in, and Fan‐out are realized through switches cascading in series or parallel. Furthermore, switch canvas strategy is explored to obtain the shortest reaction path and highest output concentration for circuits. Finally, a novel strategy of integrating computing module using molecular switches is proposed. Here, we construct a half‐adder, half‐subtractor, and a 9‐bit parity checking circuits to verify its feasibility. Compared with the classical monorail and dual‐track logic circuits, the structure scale is reduced by more than two times, and the DNA strands are decreased by more than four times, which effectively reduces the circuit complexity and raises the reaction speed. The above results show that MSC strategy has a great potential to construct large‐scale DNA circuits and provides a development model for the scalability and modularity of biological computing.

Singleton {NOT} and Doubleton {YES; NOT} Gates Act as Functionally Complete Sets in DNA-Integrated Computational Circuits.

A functionally complete Boolean operator is sufficient for computational circuits of arbitrary complexity. We connected YES (buffer) with NOT (inverter) and two NOT four-way junction (4J) DNA gates to obtain IMPLY and NAND Boolean functions, respectively, each of which represents a functionally complete gate. The results show a technological path towards creating a DNA computational circuit of arbitrary complexity based on singleton NOT or a combination of NOT and YES gates, which is not possible in electronic computers. We, therefore, concluded that DNA-based circuits and molecular computation may offer opportunities unforeseen in electronics.

Encoding Constraints as Binary Constraint Networks Satisfying BTP

Recently, the Binary Constraint Tree (BCT), a tree structured Binary Constraint Network (BCN), has been shown to be more succinct than various ad-hoc constraints. In this paper, we investigate the modelling power of a well-known tractable hybrid class generalizing BCT, i.e. the class of BCNs satisfying Broken Triangle Property (BTP) called BTP Networks (BTPNs). We show that the consistency checker of BTPN can be computed by polysize monotone circuit, thus, some global constraints cannot be encoded as polysize BTPN, such as the AllDifferent and Linear constraints. Then our study reveals that BTPN is strictly more succinct than the DNNF constraint and all 14 ad-hoc constraints discussed in (Wang and Yap 2023), such as the context-free grammar, BCT and smart table constraints. Furthermore, we also show that BTPN is as powerful as DNNF in terms of computing various operations and queries. In addition, we prove that it is NP-hard to determine the minimum sized BTPN encoding a constraint.

A Self-Oscillated Organic Synapse for In-Memory Two-Factor Authentication.

Entering the era of AI 2.0, bio-inspired target recognition facilitates life. However, target recognition may suffer from some risks when the target is hijacked. Therefore, it is significantly important to provide an encryption process prior to neuromorphic computing. In this work, enlightened from time-varied synaptic rule, an in-memory asymmetric encryption as pre-authentication is utilized with subsequent convolutional neural network (ConvNet) for target recognition, achieving in-memory two-factor authentication (IM-2FA). The unipolar self-oscillated synaptic behavior is adopted to function as in-memory asymmetric encryption, which can greatly decrease the complexity of the peripheral circuit compared to bipolar stimulation. Results show that without passing the encryption process with suitable weights at the correct time, the ConvNet for target recognition will not work properly with an extremely low accuracy lower than 0.86%, thus effectively blocking out the potential risks of involuntary access. When a set of correct weights is evolved at a suitable time, a recognition rate as high as 99.82% can be implemented for target recognition, which verifies the effectiveness of the IM-2FA strategy.

Abstract 5019: Comprehensive pan-cancer analysis of cfDNA methylation marks in tumors reveals complex epigenetic regulatory circuits and diagnostic biomarkers

Abstract Early detection of tumor activity in clinically asymptomatic patients has the potential to improve quality of life and prevent unnecessary exposure to toxic therapies. DNA methylation is one of the most studied, stable, and fundamental epigenetic marks and represents a prominent alteration in most cancers. Analysis of DNA methylation, particularly in liquid biopsies has been introduced in cancer diagnosis and risk stratification. Despite indisputable achievements, translation into clinical practice is lagging behind, primarily due to 1) challenges associated with the analysis of DNA methylation, 2) the fragmented nature of cell-free DNA (cfDNA), aggravated by bisulfite treatment, 3) lack of clinical validation of reported cfDNA methylation marks, and 4) the paucity of knowledge about the functional consequences of cfDNA methylation marks within tumors. Using a sample pooling strategy, complemented with robust whole genome and reduced representation methylation sequencing, we establish a pan-cancer cfDNA methylation resource encompassing 12 cancer entities with diverse clinical phenotypes and treatment modalities. We built this compendium using a robustly performing whole genome and reduced representaion enzymatic methylation sequencing of more than 150 cfDNA and tumor DNA. We complement our data by analyzing DNA methylation data from 15 cancer entities (more than 7,000 patients) within the TCGA. We developed an enzymatic digital PCR (dPCR) approach for pan-cancer but also entity-specific analysis of cfDNA methylation at single base-resolution. Using this dPCR assay, we analyzed cfDNA and tumor DNA samples from more than 400 patients and compared enzymatic digestion with bisulfite treatment. We demonstrate that this resource can allow for the identification of entity-agnostic and specific markers, and that cfDNA methylation patterns are mirrored in tumor samples. The approach can be applied for methylation profiling of yet unanalyzed entities. Finally, we demonstrate unconventional epigenetic regulation of gene expression by methylated DNA-binding transcription factors whose activities are tissue- and context-specific and dosage-dependent. This work, therefore, provides a reference resource to identify minimally invasive, entity-specific and pan-cancer markers applicable for diagnostics, surveillance and patient stratification. It also sets the stage for further investigation of tissue- and context-specific epigenetic regulation of gene expression in health and disease by methylated DNA-binding transcription factors. Citation Format: Smiths Sengkwawoh Lueong, Martin Metzenmacher, Gregor Zaun, Gina Lauren Mayer, Erik Jan Hemmer, Katharina Lückerath, Kelsey Pomykala, Balazs Hegedüs, Peter A. Horn, Marija Trajkovic-Arsic, Tibor Szarvas, Renáta Váraljai, Corinna Keup, Ingeborg Tinhofer, Stephen George, Sabine Kasimir-Bauer, Samuel Peña-Llopis, Alexander Roesch, Cornelius Kürten, Lukas Boosfeld, Kirsten Bruderek, Christopher Darr, Thomas Hilser, Viktor Grünwald, Sven Brandau, Boris Hadaschik, Hans Neubauer, Irene Irene Esposito Irene Esposito, Tanja Fehm, Csilla Oláh, Anita Csizmarik, Fabinshy Thangarajah, Laura Reetz, Ghanam Jamal, Basant Kumar Thakur, Halime Kalkavan, Alexander Schramm, Martin Schuler, Jens T. Siveke. Comprehensive pan-cancer analysis of cfDNA methylation marks in tumors reveals complex epigenetic regulatory circuits and diagnostic biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5019.

Inhibition of kinetic random-distribution in DNA Seesaw gates and biosensors for complete leakage prevention

DNA nanomaterials have a wide application prospect in biomedical field, among which DNA computers and biosensors based on Seesaw-based DNA circuit is considered to have the most development potential. However, the serious leakage of Seesaw-based DNA circuit prevented its further development and application. Moreover, the existing methods to suppress leakage can't achieve the ideal effect. Interestingly, we found a new source of leakage in Seesaw-based DNA circuit, which we think is the main reason why the previous methods to suppress leakage are not satisfactory. Therefore, based on this discovery, we use DNA triplex to design a new method to suppress the leakage of Seesaw-based DNA circuit. Its ingenious design makes it possible to perfectly suppress the leakage of all sources in Seesaw-based DNA circuit and ensure the normal output of the circuit. Based on this technology, we have constructed basic Seesaw module, AND gate, OR gate, secondary complex circuits and DNA detector. Experimental results show that we can increase the working range of the secondary Seesaw-based DNA circuit by five folds and keep its normal output signal above 90%, and we can improve the LOD of the Seesaw-based DNA detector to 1/11 of the traditional one(1.8pM). More importantly, we successfully developed a detector with adjustable detection range, which can theoretically achieve accurate detection in any concentration range. We believe the established triplex blocking strategy will greatly facilitate the most powerful Seesaw based DNA computers and biosensors, and further promote its application in biological systems.

Sustainable printed circuit board substrates based on flame-retarded PLA/flax composites to reduce environmental load of electronics: Quality, reliability, degradation and application tests

The present paper introduces a novel, sustainable approach to produce an eco-friendly Printed Circuit Board (PCB) substrate; a substitute for traditional substrates, to significantly reduce e-waste. We present the prepreg technology, the road to actual circuit assembly with application studies, life cycle analysis (LCA), and sustainability analysis. The flame-retarded prepregs and resulting PCB assemblies were based on polylactic acid (PLA), the structure is reinforced with flax textiles. After copper lamination, subtractive PCB production was performed, and thermal and mechanical reliability was investigated in the case of both laminated and bare substrates. Steps of surface roughness, peel and thermal analysis followed. After a new set of assemblies, the post-assembly analysis was extended with further shear strength analysis on the soldered components and mass analysis regarding thermal processes. The evaluation showed that PLA/Flax substrates provide reliable structural performance up to 200 °C in the reflow soldering process; this allows limited but stabilized application possibilities with specific eco-friendly lead-free solders. A basic blinker circuit and a field programmable gate array (FPGA)--based design was produced and tested; the latter has the general complexity of a commercial circuit. A vol% and wt% analysis extended our discussion with a reduction of harmful components in waste in the range of 90%, which is a disruptive and significant result. Life cycle analysis (LCA) quantified the ecological impact of the assembly, highlighting a significant ease on environmental load (∼10%) for the total assembly. Finally, a qualitative degradation study was introduced to the prepared samples to investigate short-term stability with mechanical-, colour-, mass- and scanning electron microscopy (structure) analysis. Early results show that the boards can withstand the harsh environment of a composting bin for a few days, but in the time of a few weeks, degradation starts, pointing to eventual decomposition. The work directly connects with multiple sustainability development goals.

Compilation of Hierarchical Transistor Circuits in SPICE Format

Software tools for compiling and decompiling descriptions of transistor circuits are widely used in computer-aided VLSI design. These two operations are inverse to each other in terms of guiding the design process. Netlist compiling a hierarchical schematics allows its specification to be converted into a functionally equivalent flat netlist. The goal of the decompilation is to reconstruct the hierarchical description of the circuit by extracting subcircuits that are gates or more complex elements. This paper examines the problem of compiling hierarchical MOS transistor circuits. The initial hierarchical schematic and resulting flat netlist are specified in SPICE format. A fast recursive algorithm for compilation of hierarchical descriptions of arbitrary nesting depth and its software implementation in C++ are proposed. During the compilation process, the ports of the circuit substituted in place of the component being compiled are renamed, as well as the names of internal nets and elements in the description of the circuit itself by adding a prefix to them that specifies the path in the hierarchy to the component being compiled. The developed compilation program was tested on a number of practical hierarchical transistor circuits as part of a transistor circuit analyzer for functional equivalence. The results of the compilation program tests make it possible to evaluate the increase in compilation time with increasing complexity of circuits and the depth of subcircuits nesting, as well as to compare the performance of the compilation procedure and its inverse procedure of decompiling the resulting flat netlist.

Hard QBFs for Merge Resolution

We prove the first genuine quantified Boolean formula (QBF) proof size lower bounds for the proof system Merge Resolution (MRes), a refutational proof system for prenex QBFs with a CNF matrix. Unlike most QBF resolution systems in the literature, proofs in MRes consist of resolution steps together with information on countermodels, which are syntactically stored in the proofs as merge maps. This makes MRes quite powerful: it has strategy extraction by design and allows short proofs for formulas that are hard for classical QBF resolution systems. Here, we show the first genuine QBF exponential lower bounds for MRes , thereby uncovering limitations of MRes. Technically, the results are either transferred from bounds from circuit complexity (for restricted versions of MRes) or directly obtained by combinatorial arguments (for full MRes). Our results imply that the MRes approach is largely orthogonal to other QBF resolution models such as the QCDCL resolution systems QRes and QURes and the expansion systems ∀ Exp + Res and IR.

Compiling Quantum Circuits for Dynamically Field-Programmable Neutral Atoms Array Processors

Dynamically field-programmable qubit arrays (DPQA) have recently emerged as a promising platform for quantum information processing. In DPQA, atomic qubits are selectively loaded into arrays of optical traps that can be reconfigured during the computation itself. Leveraging qubit transport and parallel, entangling quantum operations, different pairs of qubits, even those initially far away, can be entangled at different stages of the quantum program execution. Such reconfigurability and non-local connectivity present new challenges for compilation, especially in the layout synthesis step which places and routes the qubits and schedules the gates. In this paper, we consider a DPQA architecture that contains multiple arrays and supports 2D array movements, representing cutting-edge experimental platforms. Within this architecture, we discretize the state space and formulate layout synthesis as a satisfiability modulo theories problem, which can be solved by existing solvers optimally in terms of circuit depth. For a set of benchmark circuits generated by random graphs with complex connectivities, our compiler OLSQ-DPQA reduces the number of two-qubit entangling gates on small problem instances by 1.7x compared to optimal compilation results on a fixed planar architecture. To further improve scalability and practicality of the method, we introduce a greedy heuristic inspired by the iterative peeling approach in classical integrated circuit routing. Using a hybrid approach that combined the greedy and optimal methods, we demonstrate that our DPQA-based compiled circuits feature reduced scaling overhead compared to a grid fixed architecture, resulting in 5.1X less two-qubit gates for 90 qubit quantum circuits. These methods enable programmable, complex quantum circuits with neutral atom quantum computers, as well as informing both future compilers and future hardware choices.

3D-printed sensor electric circuits using atomic layer deposition

3D-printing, also known as additive manufacturing, has enabled the production of dynamically shaped objects often customized for specific applications. Many applications, such as sensors in the aerospace industry, have demanding mass and volume requirements or need to work in challenging environments that necessitate electronics to be protected. The combination of 3D-printing and electronics could open up new applications not feasible previously. We propose a novel manufacturing method capable of integrating a complex electric circuit consisting of several, commonly available electronic components with a 3D-printed object. This is achieved using a commercial printer and atomic layer deposition for coating. Various printable polymers and coatings were tested to identify two polymers that could be printed into one object, allowing selective conductivity when coated with conductive coating Selective conductivity is achieved when one polymer exhibits poorer and more non-continuous coating growth compared to the other. The 3D-printed object’s three-dimensional shape and details were used to create the electrical circuit and aid in achieving selective conductivity. A demonstration consisting of an ultraviolet light (UV) sensor, based on an existing traditional circuit board, was replicated using this method. The 3D-printed circuit was then tested by comparing its output with that of the original when placed under the same UV-light source. The novel circuit output closely followed the original. The presented method can combine an electric circuit with the dynamic capabilities of a 3D-printer, allowing for savings in existing applications as well as new applications.

Development and Implementation of an FPGA-Embedded Multimedia Remote Monitoring System for Information Technology Server Room Management

Conventional data acquisition systems face challenges in achieving high acquisition speeds and rapid storage of large data volumes using microcontrollers. In contrast, field-programmable gate arrays (FPGAs) offer numerous advantages, including high clock frequencies, minimal internal delays, fast operational speeds, abundant internal RAM resources, and simplified control of complex peripheral circuits. This study presents the design of an FPGA-based multimedia remote monitoring system for information technology server rooms. The proposed system utilizes an FPGA as the primary controller and incorporates environmental sensors, electrical energy sensors, carbon monoxide sensors, smoke sensors, and A/D converter modules to monitor multiple locations within the server room. Simultaneously, the FPGA transmits the collected data from each monitoring point via a serial port to an LCD serial screen for display. An alarm is triggered if any environmental anomalies are detected, indicating abnormal statuses. Additionally, the system employs the fast Fourier transform algorithm and butterfly operations to derive voltage and current AC quantities, while utilizing relative temperature differences to identify equipment faults within the server room. The system is evaluated in terms of functionality, user-friendliness, and reliability. Experimental results demonstrate that all performance measures align with expectations, fulfilling the initial design objectives and highlighting the potential applicability and relevance of FPGA technology in the monitoring field. In addition, a comparison between FPGA and traditional microcontroller systems is performed, showcasing the superior processing speed and performance of the FPGA-based system. This comparative analysis further validates the advantages of using FPGA technology in high-speed data acquisition and monitoring applications.

On Blocky Ranks Of Matrices

A matrix is blocky if it is a "blowup" of a permutation matrix. The blocky rank of a matrix M is the minimum number of blocky matrices that linearly span M. Hambardzumyan, Hatami and Hatami defined blocky rank and showed that it is connected to communication complexity and operator theory. We describe additional connections to circuit complexity and combinatorics, and we prove upper and lower bounds on blocky rank in various contexts.

Epilepsy is a complex circuit disease with a cure

Epilepsy is a complex circuit disease with a cure

Comparing performance and complexity of TCHB and CHB multilevel inverters using NLC technique

This paper presents a modulation strategy applied to a 13-level three-phase transistor clamped H-bridge (TCHB) inverter, aimed at a renewable and electric vehicle drives application. A comparison is performed between the TCHB inverter and a traditional cascaded H-bridge (CHB) inverter, considering circuit complexity, switching losses, and total harmonic distortion (THD) attained from each multilevel inverter topologies. The TCHB inverter achieves a 13-level output with only 15 switches, whereas the conventional CHB inverter requires 24 switches. The modulation technique, employing a nearest level control, yields improved output quality for both the TCHB and CHB multilevel inverters. The results demonstrate that this strategy effectively minimizes the overall THD. Notably, previous modulation techniques mainly focused on carrier-based PWM or SVPWM, making this approach distinctive. The FFT analysis reveals a voltage THD of 5.49% for TCHB and 5.15% for CHB, indicating a marginal difference in THD content for each multilevel inverter. Despite the CHB inverter experiencing double the switching stress compared to TCHB, since less switches are required in the TCHB inverter, consequently, the system's total cost and complexity are reduced. The achieved results are verified through the use of simulations carried out in the MATLAB Simulink.

Two‐Dimensional Heterostructure Complementary Logic Enabled by Optical Writing

Integrated logic circuits using atomically thin, two‐dimensional (2D) materials offer several potential advantages compared to established silicon technologies such as increased transistor density, circuit complexity, and lower energy dissipation leading to scaling benefits. In this article, a novel approach to achieve tunable doping in 2D semiconductors is explored to achieve complementary transistors and logic integration. By selectively transferring WSe2 onto hBN and SiO2 substrates, complementary transistor behavior (n‐ and p‐type) was achieved using a UV light source and electrostatic activation. Furthermore, advanced characterization techniques, including high‐resolution transmission electron microscopy (HRTEM) and Kelvin probe force microscopy (KPFM), provided insights into the chemical composition and surface potential changes after UV writing. Finally, a logic inverter was successfully implemented using selectively photo‐induced doped WSe2 transistors, showcasing the potential for practical logic applications. This innovative method opens new avenues for designing energy‐efficient and reconfigurable 2D semiconductor circuits, addressing key challenges in modern electronics.