Quantum modulation-based data search
An efficient search includes: inputting data comprising a vector that requires a first amount of memory; compressing the vector into a compressed representation while preserving information content of the vector, including: encoding, using one or more non-quantum processors, at least a portion of the vector to implement a quantum gate matrix; and modulating a reference vector using the quantum gate matrix to generate the compressed representation; searching the compressed vector in a database; and outputting a search result to be displayed, stored, and/or further processed.
1. A system, comprising:
one or more non-quantum processors configured to:
input data comprising a vector that requires a first amount of memory;
compress the vector into a compressed representation while preserving information content of the vector, including to:
encode, using the one or more non-quantum processors, at least a portion of the vector to implement a quantum gate matrix; and
modulate a reference vector using the quantum gate matrix to generate the compressed representation;
search the compressed vector in a database; and
output a search result to be displayed, stored, and/or further processed; and
one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions.
2. The system of claim 1 , wherein the database comprises compressed data.
3. The system of claim 1 , wherein the database comprises compressed data, and wherein the compressed data is obtained by:
encoding at least a portion of original database data to implement a corresponding database quantum gate matrix; and
modulating a database reference vector using the corresponding database quantum gate matrix.
4. The system of claim 1 , wherein the search is sequence-dependent.
5. The system of claim 1 , wherein the search is sequence-independent.
6. The system of claim 1 , wherein to search the compressed vector in the database includes to find a distance between the compressed vector and entries of the database.
7. The system of claim 1 , wherein the one or more non-quantum processors are further configured to cluster search results based on similarity measures of the compressed vector and entries of the database.
8. A method, comprising:
inputting data comprising a vector that requires a first amount of memory;
compressing the vector into a compressed representation while preserving information content of the vector, including:
encoding, using one or more non-quantum processors, at least a portion of the vector to implement a quantum gate matrix; and
modulating a reference vector using the quantum gate matrix to generate the compressed representation;
searching the compressed vector in a database; and
outputting a search result to be displayed, stored, and/or further processed.
9. The method of claim 8 , wherein the database comprises compressed data.
10. The method of claim 8 , wherein the database comprises compressed data, and wherein the compressed data is obtained by:
encoding at least a portion of original database data to implement a corresponding database quantum gate matrix; and
modulating a database reference vector using the corresponding database quantum gate matrix.
11. The method of claim 8 , wherein the search is sequence-dependent.
12. The method of claim 8 , wherein the search is sequence-independent.
13. The method of claim 8 , wherein searching the compressed vector in the database includes finding a distance between the compressed vector and entries of the database.
14. The method of claim 8 , further comprising clustering search results based on similarity measures of the compressed vector and entries of the database.