Quantum Sensor Initialization to Reduce VQE Iterations
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Solution Overview
Problem
Existing methods for approximating a full quantum state of a physical phenomenon, such as the energy of a molecule, require a large number of iterations, incurring significant computational and resource costs due to the need for initializing ansatz parametric circuits with random or zero states.
Innovation Solution
Initializing the ansatz parametric circuit with a sensed quantum state measured by a quantum sensor, which is more similar to the actual quantum state, reduces the number of iterations required to converge on the desired expectation value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the ansatz parametric circuit is initialized with random or zero states, then the circuit can be set up simply, but a large number of iterations are required, incurring significant computational and resource costs
Solution Approach 1:
The patent applies preliminary action by using a quantum sensor to pre-measure and prepare an initial quantum state that approximates the target state before the VQE algorithm begins. This preliminary measurement of physical quantities (such as magnetic moments or g-factor) provides a head start, reducing the number of iterations needed for convergence while maintaining measurement accuracy.
2Productivity
If the ansatz parametric circuit is initialized with a sensed quantum state, then the number of iterations is reduced, but additional quantum sensing equipment and setup are required
Solution Approach 1:
The patent applies universality by designing a hybrid quantum system where the quantum sensor serves multiple functions: it acts as both a measurement device for physical quantities and as an initialization source for the quantum computing circuit. This multi-functionality reduces the need for separate initialization equipment, thereby reducing overall device complexity while maintaining the benefit of reduced iterations.
3Measurement precision
If more iterations are performed to achieve better approximation, then measurement precision improves, but computational costs and resource consumption increase
Solution Approach 1:
The quantum sensor performs preliminary measurements of physical quantities and prepares an initial state that is already close to the target quantum state. This preliminary action significantly reduces the number of VQE iterations needed to achieve the desired measurement precision, thereby reducing computational costs and energy consumption while maintaining high accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces the number of iterations needed, thereby decreasing computational costs and resource consumption while providing a more efficient approximation of the quantum state.
Implementation Method 1
The qubits have unique features, as each qubit can be in superposition
Implementation Method 2
several qubits can be entangled
Implementation Method 3
By exploiting quantum properties such as entanglement, quantum interference, and quantum state squeezing
Implementation Method 4
By exploiting quantum properties such as entanglement, quantum interference, and quantum state squeezing
Data Source
AI summary
A system, apparatus and product comprising: a quantum sensor that is configured to measure a property of a first physical phenomenon; a quantum computer that is configured to execute a parametric quantum circuit comprising qubits that are set to represent the property of the first physical phenomenon, wherein the parametric quantum circuit comprises: an ansatz parametric circuit configured to approximate a target quantum state of a second physical phenomenon, and to output a manipulated quantum state; and an assessing module configured to assess an expectation value of operators on the manipulated quantum state; wherein said quantum computer is configured to implement a Variational Quantum Eigensolver (VQE) scheme to iteratively adjust values of a set of parameters defining the ansatz parametric circuit until the assessing module provides a desired expectation value; and an output module configured to output the desired expectation value.