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The software program is a collection of Python implementations of quantum circuits for solving linear partial differential equations using quantum signal processing. The circuits are implemented using the qiskit SDK.
Circuit automatically corrects for drifting offset voltage, providing long-term stability for current-monitoring instruments. Circuit is stable over wide temperature range; therefore, no compensation for temperature variations is necessary. Besides consuming little power, circuit introduces negligible noise on monitored lines and responds linearly to monitored circuit.
Combinations of pass transistors and logic gates driving nonlinear capacitive loads are analyzed for the presence of characteristics that will permit easier and more accurate digital logic simulation. Accurate time delay models are developed by studying the nature of the response of simplified circuit models to variations of input waveform rise and fall times and output loading. The nonlinear effects of the CMOS logic devices are minimized to permit easier interpretation of the influence of nonlinear capacitive loads. The performance of a CMOS inverter with a complex nonlinear load consisting of a pass transistor that separates a range of capacitances is compared to the same inverter circuit with a linear capacitive load to develop an understanding of the unique requirements of modeling a nonlinear system. Several methods of modeling the delay of CMOS circuits are reviewed, and a multi-parameter linear model is described. General guidelines for designing CMOS circuits with complex load circuits are developed, emphasizing that the circuit output rise delays and fall delays must be separately analyzed.
A damped linear oscillator (LRC circuit) predicts a significant amount of the AL index variations when it is driven by the IMF's B(South) component. The model parameters are determined from fitting the AL time series and show a small, apparently nonsystematic variation with the activity level. Following an isolated external disturbance the LRC model's response peaks at 15 min - 0.5 h and decays after 1-2 more hours. The time scales and the correlation between observed AL and the circuit output (60-80 percent) are in good agreement with earlier linear prediction filter results. The results support the modeling of the global magnetospheric behavior with dynamical systems of a few degrees of freedom.
Modulation multiplier provides a simple means of multiplying the width modulation of a pulse train by a constant factor. It operates directly on a pulse width modulated input signal to generate an output pulse train having a greater degree of width modulation than the input signal.
Circuit stabilizes current-transfer ratio (CTR) of optically coupled isolator used as linear transducer. New circuit employs feedback circuit containing second optocoupler. Circuit is inexpensive, requires little additional hardware.
Resistance thermometer incorporating a germanium resistance element with a platinum resistance element in a wheatstone bridge circuit has a linear temperature-resistance coefficient over a range from approximately minus 140 deg C to approximately minus 253 deg C.
The design concepts, analyses, and development of GaAs monolithic microwave integrated circuit (MMIC) linear-phase and digital modulators for the next generation of space-borne communications systems are summarized. The design approach uses a compact lumped element quadrature hybrid and Metal Semiconductor Field Effect Transistors (MESFET)-varactors to provide low loss and well-controlled phase performance for deep space transponder (DST) applications. The measured results of the MESFET-diode show a capacitance range of 2:1 under reverse bias, and a Q of 38 at 10 GHz. Three cascaded sections of hybrid-coupled reflection phase shifters were modeled and simulations performed to provide an X-band (8415 +/- 50 MHz) DST phase modulator with +/- 2.5 radians of peak phase deviation. The modulator will accommodate downlink signal modulation with composite telemetry and ranging data, with a deviation linearity tolerance of +/- 8 percent and insertion loss of less than 8 +/- 0.5 dB. The MMIC digital modulator is designed to provide greater than 10 Mb/s of bi-phase modulation at X-band.
Computer aided design of linear time invariant feedback control circuits
Surge arrester behavioral modeling for realistic systems embedded in an E1 high-altitude electromagnetic pulse environment inherently encompasses three interconnected complications: (1) the need to account for signal propagation across two domains, electromagnetics and electrical; (2) the need to include both linear and nonlinear circuit components in the analysis; and (3) the need to understand that the over-current and over-voltage mitigation performance is dependent not only on the properties of the surge arrester and protected load but also on the topology of the overall electrical network. This study presents a framework to address these challenges in a systematic manner to consider the effectiveness of protective measures for a common class of equipment in power generation facilities. Full-wave simulations were carried out to derive circuit-domain (i.e., lumped element–based) equivalent models for the excitation waveform and the physical components of the system. Then, these equivalent models were imported to a circuit solver and combined with a high-frequency surge arrester model to evaluate mitigation performance. The methodology outlined is general enough such that it can be applied for other electromagnetic interference problems that involve E2/E3 HEMP or microwave emissions.
A circuit generates sinusoidal excitation signals for a shaft-angle resolver and, like the arctangent circuit described in the preceding article, generates an analog voltage proportional to the shaft angle. The disadvantages of the circuit described in the preceding article arise from the fact that it must be made from precise analog subcircuits, including a functional block capable of implementing some trigonometric identities; this circuitry tends to be expensive, sensitive to noise, and susceptible to errors caused by temperature-induced drifts and imprecise matching of gains and phases. These disadvantages are overcome by the design of the present circuit. The present circuit (see figure) includes an excitation circuit, which generates signals Ksin(Omega(t)) and Kcos(Omega(t)) [where K is an amplitude, Omega denotes 2(pi)x a carrier frequency (the design value of which is 10 kHz), and t denotes time]. These signals are applied to the excitation terminals of a shaft-angle resolver, causing the resolver to put out signals C sin(Omega(t)-Theta) and C cos(Omega(t)-Theta). The cosine excitation signal and the cosine resolver output signal are processed through inverting comparator circuits, which are configured to function as inverting squarers, to obtain logic-level or square-wave signals .-LL[cos(Omega(t)] and -LL[cos(Omega(t)-Theta)], respectively. These signals are fed as inputs to a block containing digital logic circuits that effectively measure the phase difference (which equals Theta between the two logic-level signals). The output of this block is a pulse-width-modulated signal, PWM(Theta), the time-averaged value of which ranges from 0 to 5 VDC as Theta ranges from .180 to +180deg. PWM(Theta) is fed to a block of amplifying and level-shifting circuitry, which converts the input PWM waveform to an output waveform that switches between precise reference voltage levels of +10 and -10 V. This waveform is processed by a two-pole, low-pass filter, which removes the carrier-frequency component. The final output signal is a DC potential, proportional to Theta that ranges continuously from -10 V at Theta = -180deg to +10 V at Theta = +180deg..
Classical short-circuit programs that linearize the power network are no longer applicable for inverter based resources (IBRs), necessitating an iterative approach. Phasor domain programs can model the IBRs using an iterative approach considering nonlinear fault responses. In phasor domain models, the IBR can be modeled as a voltage controlled current source (VCCS) in tabular form with positive, negative, and zero sequence information for balanced and unbalance short-circuit faults. In the VCCS modeling of the IBR, positive and negative incremental reactive current, also known as the k-factor, plays an important role in short circuit program convergence. In this work, a few approaches: conventional VCCS modeling with a k-factor of 2, conventional VCCS modeling with a k-factor of 2 with modified pre-fault voltages, VCCS characteristics based on the power flow solution with a k-factor of 2, and VCCS characteristics based on the power flow solution with a k-factor of 1 are investigated for short circuit program convergence under higher IBR penetration. The IEEE 39 bus New England Test System is taken as the test system, and simulations are carried out in PSS®CAPE 15.0.26 simulation software. Simulation results demonstrate that IBR penetration is higher for the VCCS model, which corresponds to the power flow solution with k-factor 1, compared to other approaches.
Linear Variable Differential Transformer /LVDT/ electronic skewing circuit guides a long cylindrical capsule underwater into a larger tube so that it does not contact the tube wall. This device detects movement of the capsule from a reference point and provides a continuous signal that is monitored on an oscilloscope.
We present a hardware-reconfigurable ansatz on N q -qubits for the variational preparation of many-body states of the Anderson impurity model (AIM) with N imp + N bath = N q /2 sites, which conserves total charge and spin z component within each variational search subspace. The many-body ground state of the AIM is determined as the minimum over all minima of O(N$^2_ q$) distinct charge-spin sectors. Hamiltonian expectation values are shown to require ω(N q ) < N meas. $\leqslant$ O(N imp N bath ) symmetry-preserving, parallelizable measurement circuits, each amenable to postselection. To obtain the one-particle impurity Green’s function we show how initial Krylov vectors can be computed via midcircuit measurement and how Lanczos iterations can be computed using the symmetry-preserving ansatz. For a single-impurity Anderson model with a number of bath sites increasing from one to seven, we show using numerical emulation that the ease of variational ground-state preparation is suggestive of linear scaling in circuit depth and subquartic scaling in optimizer complexity. We therefore expect that, combined with time-dependent methods for Green’s function computation, our ansatz provides a useful tool to account for electronic correlations on early fault-tolerant processors. Finally, with a view towards computing real materials properties of interest like magnetic susceptibilities and electron-hole propagators, we provide a straightforward method to compute many-body, time-dependent correlation functions using a combination of time evolution, midcircuit measurement-conditioned operations, and the Hadamard test.
An electronic circuit is used to compare two sequences, such as genetic sequences, to determine which alignment of the sequences produces the greatest similarity. The circuit includes a linear array of series-connected processors, each of which stores a single element from one of the sequences and compares that element with each successive element in the other sequence. For each comparison, the processor generates a scoring parameter that indicates which segment ending at those two elements produces the greatest degree of similarity between the sequences. The processor uses the scoring parameter to generate a similar scoring parameter for a comparison between the stored element and the next successive element from the other sequence. The processor also delivers the scoring parameter to the next processor in the array for use in generating a similar scoring parameter for another pair of elements. The electronic circuit determines which processor and alignment of the sequences produce the scoring parameter with the highest value.
Circuit design and performance of cardiotachometer with linear indication of beat-to-beat heart rate, noting input clipping and filter circuits
Quantum computing shows great potential, but errors pose a significant challenge. This study explores new strategies for mitigating quantum errors using artificial neural networks (ANNs) and the Yang–Baxter equation (YBE). Unlike traditional error mitigation methods, which are computationally intensive, we investigate artificial error mitigation. We developed a novel method that combines ANNs for noise mitigation combined with the YBE to generate noisy data. This approach effectively reduces noise in quantum simulations, enhancing the accuracy of the results. The YBE rigorously preserves quantum correlations and symmetries in spin chain simulations in certain classes of integrable lattice models, enabling effective compression of quantum circuits while retaining linear scalability with the number of qubits. This compression facilitates both full and partial implementations, allowing the generation of noisy quantum data on hardware alongside noiseless simulations using classical platforms. By introducing controlled noise through the YBE, we enhance the data set for error mitigation. We train an ANN model on partial data from quantum simulations, demonstrating its effectiveness in mitigating errors in time-evolving quantum states, providing a scalable framework to enhance quantum computation fidelity, particularly in noisy intermediate-scale quantum (NISQ) systems. We demonstrate the efficacy of this approach by performing quantum time dynamics simulations using the Heisenberg XY Hamiltonian on real quantum devices.
Here, we present and benchmark quantum computing approaches for calculating real-time single-particle Green’s functions and nonlinear susceptibilities of Hamiltonian systems. The approaches leverage adaptive variational quantum algorithms for state preparation and propagation. Using automatically generated compact circuits, the dynamical evolution is performed over sufficiently long times to achieve adequate frequency resolution of the response functions. We showcase accurate Green’s function calculations using a statevector simulator on classical hardware for Fermi-Hubbard chains of 4 and 6 sites, with maximal ansatz circuit depths of 65 and 424 layers, respectively, and for the molecule LiH with a maximal ansatz circuit depth of 81 layers. Additionally, we consider an antiferromagnetic quantum spin-1 model that incorporates the Dzyaloshinskii-Moriya interaction to illustrate calculations of the third-order nonlinear susceptibilities, which can be measured in two-dimensional coherent spectroscopy experiments. These results demonstrate that real-time approaches using adaptive parametrized circuits to evaluate linear and nonlinear response functions can be feasible with near-term quantum processors.