GOOGLE LLC (20240296362). PERFORMING UNBIASED FERMIONIC QUANTUM MONTE CARLO CALCULATIONS USING QUANTUM COMPUTERS AND SHADOW TOMOGRAPHY simplified abstract
PERFORMING UNBIASED FERMIONIC QUANTUM MONTE CARLO CALCULATIONS USING QUANTUM COMPUTERS AND SHADOW TOMOGRAPHY
Organization Name
Inventor(s)
William Huggins of Oakland CA (US)
Joonho Lee of New York NY (US)
Ryan Babbush of Mountain View CA (US)
PERFORMING UNBIASED FERMIONIC QUANTUM MONTE CARLO CALCULATIONS USING QUANTUM COMPUTERS AND SHADOW TOMOGRAPHY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240296362 titled 'PERFORMING UNBIASED FERMIONIC QUANTUM MONTE CARLO CALCULATIONS USING QUANTUM COMPUTERS AND SHADOW TOMOGRAPHY
The abstract describes methods, systems, and apparatus for hybrid quantum-classical quantum Monte Carlo. In simple terms, this involves using a classical computer to process data from a quantum computer, which represents measurements of a trial wavefunction approximating a target wavefunction.
- Classical computer receives data from quantum computer representing trial wavefunction measurements
- Computes classical shadow of trial wavefunction using this data
- Performs imaginary time propagation for a sequence of time steps using a Hamiltonian characterizing the quantum system
- Updates wavefunction at each time step using classical shadow of trial wavefunction until convergence criteria are met
Potential Applications: - Quantum computing - Computational chemistry - Material science
Problems Solved: - Efficiently simulating quantum systems - Improving accuracy of quantum calculations
Benefits: - Faster computation of quantum systems - Enhanced accuracy in quantum simulations
Commercial Applications: Title: Quantum Simulation Software for Advanced Research Description: This technology can be used in research institutions, pharmaceutical companies, and materials science labs for advanced simulations and calculations.
Questions about Hybrid Quantum-Classical Quantum Monte Carlo: 1. How does this technology improve upon traditional quantum computing methods? 2. What are the practical implications of using a classical shadow of a trial wavefunction in quantum simulations?
Frequently Updated Research: Stay updated on the latest advancements in quantum computing and quantum simulation techniques to enhance the efficiency and accuracy of calculations.
Original Abstract Submitted
methods, systems, and apparatus for hybrid quantum-classical quantum monte carlo. in one aspect, a method includes receiving, by a classical computer, data generated by a quantum computer, the data representing results of measurements of a trial wavefunction, wherein the trial wavefunction approximates the target wavefunction and is prepared by the quantum computer, computing, by the classical computer, a classical shadow of the trial wavefunction using the data representing the results of the measurements of the trial wavefunction, and performing, by the classical computer, imaginary time propagation for a sequence of imaginary time steps of an initial wavefunction using a hamiltonian that characterizes the fermionic quantum system, wherein: the imaginary time propagation is performed until predetermined convergence criteria are met; and performing each imaginary time step of the imaginary time propagation comprises updating the wavefunction for the previous imaginary time step using the classical shadow of the trial wavefunction to obtain a wavefunction for the current imaginary time step.
