17 skills found
DavitKhach / Quantum Algorithms TutorialsTutorials for Quantum Algorithms with Qiskit implementations.
qcc4cp / QccSource code for the book "Quantum Computing for Programmers", Cambridge University Press
rubenandrebarreiro / Ibm Qiskit Global Summer School 2023⚛️ 👨🏫 📚 A two-week intensive Summer School on Quantum Computing from IBM Quantum, using mostly the features of the IBM's Qiskit library. In this Summer School, were lectured topics on basics of Quantum Information, Quantum Entanglement, Quantum Algorithms, Quantum Error Mitigation, among many others.
bastibe / MAPS ScriptsA fundamental frequency estimation algorithm using features from the magnitude and phase spectrogram.
PabloAMC / TFermionA non-Clifford gate cost assessment library of quantum phase estimation algorithms for quantum chemistry
TheGupta2012 / QPE AlgorithmsA small collection of Quantum Phase Estimation algorithms coded in python using IBM's qiskit library.
ali-ece / Design Of Optimal CMOS Ring Oscillator Using An Intelligent Optimization ToolThis paper presents an intelligent sizing method to improve the performance and efficiency of a CMOS Ring Oscillator (RO). The proposed approach is based on the simultaneous utilization of powerful and new multi-objective optimization techniques along with a circuit simulator under a data link. The proposed optimizing tool creates a perfect tradeoff between the contradictory objective functions in CMOS RO optimal design. This tool is applied for intelligent estimation of the circuit parameters (channel width of transistors), which have a decisive influence on RO specifications. Along the optimal RO design in an specified range of oscillaton frequency, the Power Consumption, Phase Noise, Figure of Merit (FoM), Integration Index, Design Cycle Time are considered as objective functions. Also, in generation of Pareto front some important issues, i.e. Overall Nondominated Vector Generation (ONVG), and Spacing (S) are considered for more effectiveness of the obtained feasible solutions in application. Four optimization algorithms called Multi-Objective Genetic Algorithm (MOGA), Multi-Objective Inclined Planes system Optimization (MOIPO), Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Modified Inclined Planes System Optimization (MOMIPO) are utilized for 0.18-mm CMOS technology with supply voltage of 1-V. Baesd on our extensive simulations and experimental results MOMIPO outperforms the best performance among other multi-objective algorithms in presented RO designing tool.
PanPalitta / Phase EstimationThis project apply reinforcement learning algorithms based on DE and PSO to optimize adaptive quantum-phase estimation.
chemsallioua / SynchroPMUA C implementation of the Phasor Measurment Unit Estimator (PMU Estimator) based on the Iterative Interpolated DFT Synchrophasor Estimation Algorithm.
wgcban / Complete State Estimation AlgorithmA Complete State Estimation Algorithm for a Three-Phase Four-Wire Low Voltage Distribution System with High Penetration of Solar PV
nelsonfilipecosta / Adaptive Quantum Phase EstimationCode used to obtain the results presented in the paper "Benchmarking machine learning algorithms for adaptive quantum phase estimation with noisy intermediate-scale quantum sensors" published in EPJ Quantum Technology on June 3, 2021.
rzcao / Inverse Matrix Phase AlgorithmThe inverse matrix based phase estimation algorithm for structured illumination microscopy (SIM).
18520339 / Uts Quantum ComputingInteractive Showcases of Quantum Tic-Tac-Toe Game and Shor's Algorithm for Integer Factorization, covering various Quantum Computing concepts like Quantum Gates, Superposition & Entanglement, Measurement & Collapse, or Quantum Fourier Transform & Phase Estimation, etc.
vtnsi / PywaspgenA toolkit for simulating stochastic and/or deterministic radio frequency aggregate spectrum (in both in-phase/quadrature and image formats) for testing sensing algorithms (e.g. detection, parameter estimation, classification).
vuritiaditya / Software EstimationPrediction of software development cost is an extremely important task before starting the actual development phase. Software products are acceptable by clients as long as they are developed within the lower budget. Software estimation is one of the most challenging areas of project management. Machine learning algorithms are used to handle these type of problems. Machine learning algorithms increase project success rates. software simulation using machine learning algorithms could further enhance project estimation methods and contribute to better resource allocation and utilization. The proposed effort and duration estimation models are intended to serve as a decision support tool for any organization developing and implementing software systems. ISBSG dataset is used for this implementation. Results show that machine learning models can be used to predict software cost with high accuracy rate. Keywords : ISBSG,Software project estimation,Effort and duration estimation, Prediction.
flaviogrando / Prony Based AlgorithmsAmplitude and phase estimations using Prony based algorithms
zhiyanding / Phase Estimation MethodsComparison of different phase estimation algorithms
