Automatic Quantum Database Search Using Amplitude Amplification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional search algorithms are inefficient when searching large object databases, as they require knowledge of the database size and struggle with determining the optimal number of amplitude amplification iterations, especially when the size is unknown.
Innovation Solution
A method that uses a combination of classical and quantum processors to measure amplitudes in a quantum circuit, performing amplitude amplifications and verification operations to locate a target object in an object database, with the number of amplifications adjusted based on the database size, allowing for automatic quantum searching without prior knowledge of the database size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional search algorithms are used to search large object databases, then the search can be performed with classical processors, but the search efficiency is low and it requires prior knowledge of the database size to determine optimal iterations
Solution Approach 1:
The patent replaces conventional classical search algorithms with quantum search algorithms that utilize quantum mechanical principles (superposition and entanglement) to achieve faster search speeds. The quantum processor performs searches in parallel across multiple states simultaneously, eliminating the need for iterative determination of optimal search parameters based on database size.
Solution Approach 2:
The patent changes the fundamental parameters of the search system by transitioning from classical bits to quantum bits (qubits), enabling the system to represent and process multiple database states simultaneously. This parameter change allows the quantum search algorithm to achieve quadratic speedup without requiring prior knowledge of database size for optimization.
2Adaptability or versatility
If the size of the object database is unknown, then the system can handle variable database sizes, but it becomes difficult to determine the optimal number of amplitude amplification iterations
Solution Approach 1:
The quantum search algorithm is self-adapting in that it automatically achieves optimal search performance regardless of database size. The algorithm's structure inherently provides the correct number of iterations through its quantum mechanical operations, eliminating the need for external parameter tuning or prior knowledge of database dimensions.
Solution Approach 2:
The quantum search algorithm performs preliminary quantum state preparation that creates a uniform superposition of all database states. This preliminary action sets up the system so that subsequent amplitude amplification operations automatically converge to the correct solution without requiring iterative adjustment based on database size.
3Speed
If amplitude amplification is performed with insufficient iterations, then the quantum processor operates faster, but the search accuracy decreases
Solution Approach 1:
The quantum search algorithm employs periodic amplitude amplification operations that systematically increase the probability amplitude of the target state. The periodic application of these operations ensures that the algorithm reaches optimal accuracy at a predetermined number of iterations, balancing speed and precision without requiring trial-and-error adjustment.
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 enables efficient and automatic quantum searching of object databases by iteratively refining the search process, ensuring the target object is found with a reduced number of amplitude amplifications, improving search efficiency and adaptability.
Implementation Method 1
Superposition means that each qubit can represent both a 1 and a 0 at the same time
Implementation Method 2
Entanglement means that qubits in a superposition can be correlated with each other in a non-classical way
Implementation Method 3
The two reflections produce a rotation of the initial state |s closer to the target object state |t. The amplitude amplification process is repeated a number of iterations to find the location of the target object
Data Source
AI summary
A method includes measuring an amplitude of a state of a quantum circuit, the amplitude corresponding to a first location in an object database. In the embodiment, the method includes executing, using a classical processor and a first memory, a verification operation, responsive to measuring the amplitude, to verify a target object in the first location. In the embodiment, the method includes re-measuring a second amplitude of a second state of the quantum circuit, the second amplitude having undergone a first plurality of amplitude amplifications, the second amplitude corresponding to a second location in the object database, the second location being verified as the target object, and wherein a total number of the first plurality of amplitude amplifications being less than a square root of a set of objects in the object database.