DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because
the claims, 8-14, are explicitly directed to a computer program perse with no embodying non-transitory computer readable medium to be executed by a processor. Since the computer program, as recited, does not appear to fall within the statutory categories of 35 U.S.C. 101 (i.e., process, machine, manufacture, or composition of matter), the claim is ineligible under 35 U.S.C. 101.
Re claims 8-14:
8. A computer program product for enabling quantum machine learning to be used effectively with classical data, the computer program product comprising one or more computer readable storage mediums having program code embodied therewith, the program code comprising programming instructions for: receiving said classical data; mapping said classical data into a quantum state space forming quantum data using a classical machine learning model; and performing said quantum machine learning on a quantum computer using said formed quantum data.
9. The computer program product as recited in claim 8, wherein the program code further comprises the programming instructions for: receiving data points of said classical data; generating different views of said data points of said classical data; encoding said different views of said data points of said classical data by an encoder to representations; comparing a similarity of said representations among said different views of said data points of said classical data to form a similarity measure; and optimizing parameters of said encoder using said similarity measure.
10. The computer program product as recited in claim 9, wherein said representations correspond to quantum state representations derived from quantum circuit operations.
11. The computer program product as recited in claim 9, wherein said different views of said data points of said classical data are generated via corruption of said classical data or corruption of an initial encoded quantum state representation by quantum hardware noise.
12. The computer program product as recited in claim 9, wherein said parameters of said encoder are optimized using said similarity measure such that a final quantum state representation of said different views of said data points of said classical data has a property that a representation of a first data point of said classical data is more similar to a representation of a corrupted view of said first data point of said classical data on average than a similarity between said representation of said first data point of said classical data and a representation of a corrupted view of other data points of said classical data.
13. The computer program product as recited in claim 9, wherein said data points of said classical data correspond to a first type of data, wherein said encoder is trained to encode different views of other data points of said first type of data of said classical data across different data sets.
14. The computer program product as recited in claim 9, wherein said representations correspond to quantum state representations or new classical representations.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7, 8-14 and 15-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In the independent and dependent claims, as recited, it is not clear what exactly is meant by quantum machine learning; should this read quantum machine learning model?
1. A method for enabling quantum machine learning to be used effectively with classical data, the method comprising: receiving said classical data; mapping said classical data into a quantum state space forming quantum data using a classical machine learning model; and performing said quantum machine learning on a quantum computer using said formed quantum data.
Claims 2-7 are also indefinite as they too depend from claim 1, ultimately.
8. A computer program product for enabling quantum machine learning to be used effectively with classical data, the computer program product comprising one or more computer readable storage mediums having program code embodied therewith, the program code comprising programming instructions for: receiving said classical data; mapping said classical data into a quantum state space forming quantum data using a classical machine learning model; and performing said quantum machine learning on a quantum computer using said formed quantum data.
Claims 9-14 are also indefinite as they too depend from claim 8, ultimately.
15. A system, comprising: a memory for storing a computer program for enabling quantum machine learning to be used effectively with classical data; and a processor connected to said memory, wherein said processor is configured to execute program instructions of the computer program comprising: receiving said classical data; mapping said classical data into a quantum state space forming quantum data using a classical machine learning model; and performing said quantum machine learning on a quantum computer using said formed quantum data.
Claims 16-20 are also indefinite as they too depend from claim 15, ultimately.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 8 and 15 is/are rejected under 35 U.S.C. 102(a)(1)as being anticipated by Henderson et al(NPL Quanvolutional Neural Networks: Powering Image Recognition with Quantum Circuits, QxBranch, arXiv:1904.04767v1 [quant-ph] 9 Apr 2019)
Re claim 1, 8 and 15 : please see figure below:
A quantum machine learning network stack is shown, see figure, that makes use of classical data(INPUT DATA).
The data is mapped, i.e., classical data is passed thru the quanvolutional layers, a quantum state space to form quantum data (figure 1b)using a classical machine learning model(see downstream classic convolutional layers);
The QNN model/ A hybrid quantum machine learning on a quantum computer using said formed quantum data is provided for.
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The method steps being inherent by virtue of the process flow diagram above as described.
Allowable Subject Matter
Claims 2-7 and 16-20 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARNOLD M KINKEAD whose telephone number is (571)272-1763. The examiner can normally be reached M-F 7am-5:30pm(Fri-Flex).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Menatoallah Youssef can be reached at 571-270-3684. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ARNOLD M. KINKEAD
Primary Examiner
Art Unit 2849
/ARNOLD M KINKEAD/Primary Examiner, Art Unit 2849