DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to the Application filed on 10/19/2023. Claims 1-20 are pending in the case. Claims 1, 9, and 17 are independent claims.
Claim Rejections - 35 U.S.C. § 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.
Claims 1-6, 9-14, and 17-20 are rejected under 35 U.S.C. § 102(a)(1) as being anticipated by Smart et al. (“Relaxation of stationary states on a quantum computer yields a unique spectroscopic fingerprint of the computer’s noise,” 15 February 2022, https://doi.org/10.1038/s42005-022-00803-8 https://www.nature.com/articles/s42005-022-00803-8, hereinafter Smart).
As to independent claim 1, Smart discloses a method for optimizing development of a quantum circuit or a quantum model on a first quantum system for later use on a second quantum system, the method comprising:
obtaining operational and performance data from said first and second quantum systems (“Ground-state populations n0 obtained from simulated time evolution with different devices and qubits (indicated by the ith qubit Qi). Systems were initialized in the |1⟩ state and evolved for time t with Hamiltonian
H
=
ω
σ
z
,” page 3 column right caption “Fig. 3 Demonstration of simulated time evolution for different devices and qubits”);
generating a first noise fingerprint for said first quantum system and a second noise fingerprint for said second quantum system based on said obtained operational and performance data from said first and second quantum systems, respectively (“we simulate stationary states on a quantum computer to obtain a unique spectroscopic fingerprint,” page 2 column left paragraph 4 lines 1-2); and
adjusting parameters of said first quantum system until a difference between said first noise fingerprint of said first quantum system and said second noise fingerprint of said second quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14) is below a threshold value (“The precise time dependence of the open quantum system depends upon the nature of the bath. If the relaxation of the bath is fast relative to the dynamics of the system, then the quantum dynamics is purely dissipative and described as Markovian, but if the dynamics of the bath and system are on the same timescale, then the dynamics causes energy to be exchanged both to and from the bath and is described as non-Markovian11,13,20. In non-Markovian dynamics the more complex interaction between the system and bath causes the system to develop a memory of its state as a function of time,” page 2 column left paragraph 2 lines 6-15).
As to dependent claim 2, Smart further discloses a method wherein said operational and performance data comprises one or more of the following selected from the group consisting of: historical calibration data, current calibration data, system settings, a quantum processor temperature, pulse settings, qubit coherence times, qubit errors, qubit and quantum gate fidelity, gate errors, thermal relation times, dephasing times, performance history of quantum circuits, noise types, and noise strengths (“we simulate stationary states on a quantum computer to obtain a unique spectroscopic fingerprint of the computer’s noise. If a quantum system in a stationary state is simulated on an ideal quantum computer, the quantum system will remain in that stationary state for all time. However, if the same system is simulated on a noisy intermediate-scale quantum (NISQ) computer, the noise causes the simulated state to become non-stationary. The resulting time dependence in the frame of the simulation provides us with a frequency profile of the noise as it is experienced by the simulated stationary quantum state,” page 2 column left paragraph 4 lines 1-10).
As to dependent claim 3, Smart further discloses a method wherein said first and second noise fingerprints are represented by eigenvectors that are created based on said operational and performance data of said first and second quantum systems, respectively (“The spectral density with respect to a quantum noise source A can be characterized as49:
S
A
ω
=
∫
-
∞
∞
d
τ
e
x
p
i
ω
τ
∑
α
β
ρ
α
α
⟨
α
A
τ
β
⟩
⟨
β
A
0
α
⟩
=
2
π
∑
α
,
β
ρ
α
α
A
α
β
2
δ
(
ϵ
β
-
ϵ
α
-
ω
)
where α and β are energy eigenstates of H and ρ represents the density matrix,” page 3 column left paragraph 1 lines 1-6).
As to dependent claim 4, Smart further discloses a method comprising determining compatibility between said first and second quantum systems based on said operational and performance data from said first and second quantum systems (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14), wherein said first quantum system is compatible with said second quantum system in response to at least a portion of a coupling map of said first quantum system being within a threshold degree of similarity to at least a portion of a coupling map of said second quantum system or in response to a qubit coherence time and a gate fidelity on matching portions of coupling maps of said first and second quantum systems being the same or better on said first quantum system than said second quantum system (“The precise time dependence of the open quantum system depends upon the nature of the bath. If the relaxation of the bath is fast relative to the dynamics of the system, then the quantum dynamics is purely dissipative and described as Markovian, but if the dynamics of the bath and system are on the same timescale, then the dynamics causes energy to be exchanged both to and from the bath and is described as non-Markovian11,13,20. In non-Markovian dynamics the more complex interaction between the system and bath causes the system to develop a memory of its state as a function of time,” page 2 column left paragraph 2 lines 6-15).
As to dependent claim 5, Smart further discloses a method wherein said parameters comprise one or more of the following selected from the group consisting of: pulse amplification, pulse attenuation, pulse modulation, pulse signal mixing, radio frequency radiated frequency, radio frequency transmit power, temperature setting of a quantum refrigerator, environmental temperature, environmental humidity, environmental pressure, vibration frequency, and vibration amplitude (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14).
As to dependent claim 6, Smart further discloses a method wherein said parameters of said first quantum system are adjusted to increase noise on said first quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14).
As to independent claim 9, Smart discloses a computer program product for optimizing development of a quantum circuit or a quantum model on a first quantum system for later use on a second quantum system, the computer program product comprising one or more computer readable storage mediums having program code embodied therewith (“computers,” page 2 column left paragraph 4 line 15), the program code comprising programming instructions for:
obtaining operational and performance data from said first and second quantum systems (“Ground-state populations n0 obtained from simulated time evolution with different devices and qubits (indicated by the ith qubit Qi). Systems were initialized in the |1⟩ state and evolved for time t with Hamiltonian
H
=
ω
σ
z
,” page 3 column right caption “Fig. 3 Demonstration of simulated time evolution for different devices and qubits”);
generating a first noise fingerprint for said first quantum system and a second noise fingerprint for said second quantum system based on said obtained operational and performance data from said first and second quantum systems, respectively (“we simulate stationary states on a quantum computer to obtain a unique spectroscopic fingerprint,” page 2 column left paragraph 4 lines 1-2); and
adjusting parameters of said first quantum system until a difference between said first noise fingerprint of said first quantum system and said second noise fingerprint of said second quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14) is below a threshold value (“The precise time dependence of the open quantum system depends upon the nature of the bath. If the relaxation of the bath is fast relative to the dynamics of the system, then the quantum dynamics is purely dissipative and described as Markovian, but if the dynamics of the bath and system are on the same timescale, then the dynamics causes energy to be exchanged both to and from the bath and is described as non-Markovian11,13,20. In non-Markovian dynamics the more complex interaction between the system and bath causes the system to develop a memory of its state as a function of time,” page 2 column left paragraph 2 lines 6-15).
As to dependent claim 10, Smart further discloses a computer program product wherein said operational and performance data comprises one or more of the following selected from the group consisting of: historical calibration data, current calibration data, system settings, a quantum processor temperature, pulse settings, qubit coherence times, qubit errors, qubit and quantum gate fidelity, gate errors, thermal relation times, dephasing times, performance history of quantum circuits, noise types, and noise strengths (“we simulate stationary states on a quantum computer to obtain a unique spectroscopic fingerprint of the computer’s noise. If a quantum system in a stationary state is simulated on an ideal quantum computer, the quantum system will remain in that stationary state for all time. However, if the same system is simulated on a noisy intermediate-scale quantum (NISQ) computer, the noise causes the simulated state to become non-stationary. The resulting time dependence in the frame of the simulation provides us with a frequency profile of the noise as it is experienced by the simulated stationary quantum state,” page 2 column left paragraph 4 lines 1-10).
As to dependent claim 11, Smart further discloses a computer program product wherein said first and second noise fingerprints are represented by eigenvectors that are created based on said operational and performance data of said first and second quantum systems, respectively (“The spectral density with respect to a quantum noise source A can be characterized as49:
S
A
ω
=
∫
-
∞
∞
d
τ
e
x
p
i
ω
τ
∑
α
β
ρ
α
α
⟨
α
A
τ
β
⟩
⟨
β
A
0
α
⟩
=
2
π
∑
α
,
β
ρ
α
α
A
α
β
2
δ
(
ϵ
β
-
ϵ
α
-
ω
)
where α and β are energy eigenstates of H and ρ represents the density matrix,” page 3 column left paragraph 1 lines 1-6).
As to dependent claim 12, Smart further discloses a computer program product wherein the program code further comprises the programming instructions for determining compatibility between said first and second quantum systems based on said operational and performance data from said first and second quantum systems (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14), wherein said first quantum system is compatible with said second quantum system in response to at least a portion of a coupling map of said first quantum system being within a threshold degree of similarity to at least a portion of a coupling map of said second quantum system or in response to a qubit coherence time and a gate fidelity on matching portions of coupling maps of said first and second quantum systems being the same or better on said first quantum system than said second quantum system (“The precise time dependence of the open quantum system depends upon the nature of the bath. If the relaxation of the bath is fast relative to the dynamics of the system, then the quantum dynamics is purely dissipative and described as Markovian, but if the dynamics of the bath and system are on the same timescale, then the dynamics causes energy to be exchanged both to and from the bath and is described as non-Markovian11,13,20. In non-Markovian dynamics the more complex interaction between the system and bath causes the system to develop a memory of its state as a function of time,” page 2 column left paragraph 2 lines 6-15).
As to dependent claim 13, Smart further discloses a computer program product wherein said parameters comprise one or more of the following selected from the group consisting of: pulse amplification, pulse attenuation, pulse modulation, pulse signal mixing, radio frequency radiated frequency, radio frequency transmit power, temperature setting of a quantum refrigerator, environmental temperature, environmental humidity, environmental pressure, vibration frequency, and vibration amplitude (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14).
As to dependent claim 14, Smart further discloses a computer program product wherein said parameters of said first quantum system are adjusted to increase noise on said first quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14).
As to independent claim 17, Smart discloses a system, comprising:
a memory for storing a computer program (“computers,” page 2 column left paragraph 4 line 15) for optimizing development of a quantum circuit or a quantum model on a first quantum system for later use on a second quantum system; and
a processor connected to said memory (“computers,” page 2 column left paragraph 4 line 15), wherein said processor is configured to execute program instructions of the computer program comprising:
obtaining operational and performance data from said first and second quantum systems (“Ground-state populations n0 obtained from simulated time evolution with different devices and qubits (indicated by the ith qubit Qi). Systems were initialized in the |1⟩ state and evolved for time t with Hamiltonian
H
=
ω
σ
z
,” page 3 column right caption “Fig. 3 Demonstration of simulated time evolution for different devices and qubits”);
generating a first noise fingerprint for said first quantum system and a second noise fingerprint for said second quantum system based on said obtained operational and performance data from said first and second quantum systems, respectively (“we simulate stationary states on a quantum computer to obtain a unique spectroscopic fingerprint,” page 2 column left paragraph 4 lines 1-2); and
adjusting parameters of said first quantum system until a difference between said first noise fingerprint of said first quantum system and said second noise fingerprint of said second quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14) is below a threshold value (“The precise time dependence of the open quantum system depends upon the nature of the bath. If the relaxation of the bath is fast relative to the dynamics of the system, then the quantum dynamics is purely dissipative and described as Markovian, but if the dynamics of the bath and system are on the same timescale, then the dynamics causes energy to be exchanged both to and from the bath and is described as non-Markovian11,13,20. In non-Markovian dynamics the more complex interaction between the system and bath causes the system to develop a memory of its state as a function of time,” page 2 column left paragraph 2 lines 6-15).
As to dependent claim 18, Smart further discloses a system wherein said operational and performance data comprises one or more of the following selected from the group consisting of: historical calibration data, current calibration data, system settings, a quantum processor temperature, pulse settings, qubit coherence times, qubit errors, qubit and quantum gate fidelity, gate errors, thermal relation times, dephasing times, performance history of quantum circuits, noise types, and noise strengths (“we simulate stationary states on a quantum computer to obtain a unique spectroscopic fingerprint of the computer’s noise. If a quantum system in a stationary state is simulated on an ideal quantum computer, the quantum system will remain in that stationary state for all time. However, if the same system is simulated on a noisy intermediate-scale quantum (NISQ) computer, the noise causes the simulated state to become non-stationary. The resulting time dependence in the frame of the simulation provides us with a frequency profile of the noise as it is experienced by the simulated stationary quantum state,” page 2 column left paragraph 4 lines 1-10).
As to dependent claim 19, Smart further discloses a system wherein said first and second noise fingerprints are represented by eigenvectors that are created based on said operational and performance data of said first and second quantum systems, respectively (“The spectral density with respect to a quantum noise source A can be characterized as49:
S
A
ω
=
∫
-
∞
∞
d
τ
e
x
p
i
ω
τ
∑
α
β
ρ
α
α
⟨
α
A
τ
β
⟩
⟨
β
A
0
α
⟩
=
2
π
∑
α
,
β
ρ
α
α
A
α
β
2
δ
(
ϵ
β
-
ϵ
α
-
ω
)
where α and β are energy eigenstates of H and ρ represents the density matrix,” page 3 column left paragraph 1 lines 1-6).
As to dependent claim 20, Smart further discloses a system wherein the program instructions of the computer program further comprise determining compatibility between said first and second quantum systems based on said operational and performance data from said first and second quantum systems (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14), wherein said first quantum system is compatible with said second quantum system in response to at least a portion of a coupling map of said first quantum system being within a threshold degree of similarity to at least a portion of a coupling map of said second quantum system or in response to a qubit coherence time and a gate fidelity on matching portions of coupling maps of said first and second quantum systems being the same or better on said first quantum system than said second quantum system (“The precise time dependence of the open quantum system depends upon the nature of the bath. If the relaxation of the bath is fast relative to the dynamics of the system, then the quantum dynamics is purely dissipative and described as Markovian, but if the dynamics of the bath and system are on the same timescale, then the dynamics causes energy to be exchanged both to and from the bath and is described as non-Markovian11,13,20. In non-Markovian dynamics the more complex interaction between the system and bath causes the system to develop a memory of its state as a function of time,” page 2 column left paragraph 2 lines 6-15).
Claim Rejections - 35 U.S.C. § 103
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 35 U.S.C. § 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 C.F.R. § 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. § 102(b)(2)(C) for any potential 35 U.S.C. § 102(a)(2) prior art against the later invention.
Claims 7 and 15 are rejected under 35 U.S.C. § 103 as being unpatentable over Smart in view of Redmond et al. (US 2022/0147824 A1, hereinafter Redmond).
As to dependent claim 7, the rejection of claim 1 is incorporated. Smart further teaches a method [] to compare said first noise fingerprint of said first quantum system with said second noise fingerprint of said second quantum system to output one or more parameter adjustments of said first quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14).
Smart does not appear to expressly teach a method wherein an artificial intelligence model is used [to analyze quantum noise].
Redmond teaches a method wherein an artificial intelligence model is used [to analyze quantum noise] (“implement an artificial neural network (ANN), and injecting the unitary quantum noise output signal into one or more layers of the ANN,” paragraph 0038 lines 7-10).
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the comparison of Smart to comprise the artificial intelligence model of Redmond. (1) The Examiner finds that the prior art included each claim element listed above, although not necessarily in a single prior art reference, with the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference. (2) The Examiner finds that one of ordinary skill in the art could have combined the elements as claimed by known software development methods, and that in combination, each element merely performs the same function as it does separately. (3) The Examiner finds that one of ordinary skill in the art would have recognized that the results of the combination were predictable, namely using an artificial intelligence model to analyze quantum noise (“implement an artificial neural network (ANN), and injecting the unitary quantum noise output signal into one or more layers of the ANN,” Redmond paragraph 0038 lines 7-10). Therefore, the rationale to support a conclusion that the claim would have been obvious is that the combining prior art elements according to known methods to yield predictable results to one of ordinary skill in the art. See MPEP § 2143(I)(A).
As to dependent claim 15, the rejection of claim 9 is incorporated. Smart further teaches a computer program product [] to compare said first noise fingerprint of said first quantum system with said second noise fingerprint of said second quantum system to output one or more parameter adjustments of said first quantum system (“By identifying frequencies of interest on the qubits themselves, we can construct systems which respond uniquely to the bath, allowing for selective transitions between different eigenstates of the system. With this in mind, we first simulate a two-qubit system with a local Hamiltonian defined by:
H
ω
1
,
ω
2
=
ω
1
σ
z
1
+
ω
2
σ
z
2
where
σ
z
j
refers to the Pauli-Z matrix in Eq. (2) acting on the
j
th qubit. This Hamiltonian has the computational basis as its energy eigenbasis, and it can be shown that changing a frequency
ω
i
can lead to a small energy transition between states differing locally on qubit
i
. By scanning over single-qubit frequencies, we can obtain a simple noise profile, and then choose appropriate
ω
i
to influence the system,” page 4 column left section “Two-qubit Hamiltonians” lines 1-14).
Smart does not appear to expressly teach a computer program product wherein an artificial intelligence model is used [to analyze quantum noise].
Redmond teaches a computer program product wherein an artificial intelligence model is used [to analyze quantum noise] (“implement an artificial neural network (ANN), and injecting the unitary quantum noise output signal into one or more layers of the ANN,” paragraph 0038 lines 7-10).
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the comparison of Smart to comprise the artificial intelligence model of Redmond. (1) The Examiner finds that the prior art included each claim element listed above, although not necessarily in a single prior art reference, with the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference. (2) The Examiner finds that one of ordinary skill in the art could have combined the elements as claimed by known software development methods, and that in combination, each element merely performs the same function as it does separately. (3) The Examiner finds that one of ordinary skill in the art would have recognized that the results of the combination were predictable, namely using an artificial intelligence model to analyze quantum noise (“implement an artificial neural network (ANN), and injecting the unitary quantum noise output signal into one or more layers of the ANN,” Redmond paragraph 0038 lines 7-10). Therefore, the rationale to support a conclusion that the claim would have been obvious is that the combining prior art elements according to known methods to yield predictable results to one of ordinary skill in the art. See MPEP § 2143(I)(A).
Claims 8 and 16 are rejected under 35 U.S.C. § 103 as being unpatentable over Smart in view of Flöther et al. (US 2023/0376577 A1, hereinafter Flöther).
As to dependent claim 8, the rejection of claim 1 is incorporated. Smart further teaches a method comprising [data] pertaining to adjustments of said parameters of said first quantum storage to models subsequently developed on said first quantum system to specify deviations to be expected when said models are executed on said second quantum system in response to said difference between said first noise fingerprint of said first quantum system and said second noise fingerprint of said second quantum system not being below said threshold value (“examining the spectral profile of the bath from the simulation of stationary quantum states may provide a unique spectroscopic fingerprint of the quantum computer. With such a fingerprint we may be able to design simulation algorithms that account for this fingerprint, providing a potentially elegant approach to error mitigation for real-world applications,” page 5 column right paragraph 1 lines 5-10; “Spectroscopic analysis of this time evolution provides a frequency spectrum—a spectroscopic fingerprint—of the noise of the effective bath induced by the quantum computer. Understanding the noise profile may allow us to create parameterized systems in which we influence state transitions with the quantum device serving as a non-Markovian bath,” page 5 column right paragraph 3 lines 5-11)
Smart does not appear to expressly teach a method comprising attaching metadata [pertaining to parameters].
Flöther teaches a method comprising attaching metadata [pertaining to parameters] (“metadata of the quantum model developed with a quantum computer is extracted. ‘Metadata,’ as used herein, refers to data that provides information about other data. Examples of such extracted metadata include, but not limited to, a degree of entanglement, quantum Fisher information, geometric differences, an expected impact of noise on the quantum model, a quantum circuit expressed in a quantum programming language, and classical model performance parameters on a fixed dataset. A digital fingerprint of the quantum model may then be constructed based on the extracted metadata. A ‘digital fingerprint,’ as used herein, maps the extracted metadata to a much shorter bit string. Author information (e.g., author(s) who trained the quantum model, company name, unique code) is then merged with the constructed digital fingerprint to form the watermark data. The watermark data is encrypted, such as by using AES with a secret key and Base64 encoding, and then stored in qubits and/or weights of the quantum model,” paragraph 0034 lines 5-22).
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the data of Smart to comprise the attached metadata of Flöther. (1) The Examiner finds that the prior art included each claim element listed above, although not necessarily in a single prior art reference, with the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference. (2) The Examiner finds that one of ordinary skill in the art could have combined the elements as claimed by known software development methods, and that in combination, each element merely performs the same function as it does separately. (3) The Examiner finds that one of ordinary skill in the art would have recognized that the results of the combination were predictable, namely storing the data with the model (“metadata of the quantum model developed with a quantum computer is extracted. ‘Metadata,’ as used herein, refers to data that provides information about other data. Examples of such extracted metadata include, but not limited to, a degree of entanglement, quantum Fisher information, geometric differences, an expected impact of noise on the quantum model, a quantum circuit expressed in a quantum programming language, and classical model performance parameters on a fixed dataset. A digital fingerprint of the quantum model may then be constructed based on the extracted metadata. A ‘digital fingerprint,’ as used herein, maps the extracted metadata to a much shorter bit string. Author information (e.g., author(s) who trained the quantum model, company name, unique code) is then merged with the constructed digital fingerprint to form the watermark data. The watermark data is encrypted, such as by using AES with a secret key and Base64 encoding, and then stored in qubits and/or weights of the quantum model,” Flöther paragraph 0034 lines 5-22). Therefore, the rationale to support a conclusion that the claim would have been obvious is that the combining prior art elements according to known methods to yield predictable results to one of ordinary skill in the art. See MPEP § 2143(I)(A).
As to dependent claim 16, the rejection of claim 1 is incorporated. Smart further teaches a computer program product comprising [data] pertaining to adjustments of said parameters of said first quantum storage to models subsequently developed on said first quantum system to specify deviations to be expected when said models are executed on said second quantum system in response to said difference between said first noise fingerprint of said first quantum system and said second noise fingerprint of said second quantum system not being below said threshold value (“examining the spectral profile of the bath from the simulation of stationary quantum states may provide a unique spectroscopic fingerprint of the quantum computer. With such a fingerprint we may be able to design simulation algorithms that account for this fingerprint, providing a potentially elegant approach to error mitigation for real-world applications,” page 5 column right paragraph 1 lines 5-10; “Spectroscopic analysis of this time evolution provides a frequency spectrum—a spectroscopic fingerprint—of the noise of the effective bath induced by the quantum computer. Understanding the noise profile may allow us to create parameterized systems in which we influence state transitions with the quantum device serving as a non-Markovian bath,” page 5 column right paragraph 3 lines 5-11)
Smart does not appear to expressly teach a computer program product comprising attaching metadata [pertaining to parameters].
Flöther teaches a computer program product comprising attaching metadata [pertaining to parameters] (“metadata of the quantum model developed with a quantum computer is extracted. ‘Metadata,’ as used herein, refers to data that provides information about other data. Examples of such extracted metadata include, but not limited to, a degree of entanglement, quantum Fisher information, geometric differences, an expected impact of noise on the quantum model, a quantum circuit expressed in a quantum programming language, and classical model performance parameters on a fixed dataset. A digital fingerprint of the quantum model may then be constructed based on the extracted metadata. A ‘digital fingerprint,’ as used herein, maps the extracted metadata to a much shorter bit string. Author information (e.g., author(s) who trained the quantum model, company name, unique code) is then merged with the constructed digital fingerprint to form the watermark data. The watermark data is encrypted, such as by using AES with a secret key and Base64 encoding, and then stored in qubits and/or weights of the quantum model,” paragraph 0034 lines 5-22).
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the data of Smart to comprise the attached metadata of Flöther. (1) The Examiner finds that the prior art included each claim element listed above, although not necessarily in a single prior art reference, with the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference. (2) The Examiner finds that one of ordinary skill in the art could have combined the elements as claimed by known software development methods, and that in combination, each element merely performs the same function as it does separately. (3) The Examiner finds that one of ordinary skill in the art would have recognized that the results of the combination were predictable, namely storing the data with the model (“metadata of the quantum model developed with a quantum computer is extracted. ‘Metadata,’ as used herein, refers to data that provides information about other data. Examples of such extracted metadata include, but not limited to, a degree of entanglement, quantum Fisher information, geometric differences, an expected impact of noise on the quantum model, a quantum circuit expressed in a quantum programming language, and classical model performance parameters on a fixed dataset. A digital fingerprint of the quantum model may then be constructed based on the extracted metadata. A ‘digital fingerprint,’ as used herein, maps the extracted metadata to a much shorter bit string. Author information (e.g., author(s) who trained the quantum model, company name, unique code) is then merged with the constructed digital fingerprint to form the watermark data. The watermark data is encrypted, such as by using AES with a secret key and Base64 encoding, and then stored in qubits and/or weights of the quantum model,” Flöther paragraph 0034 lines 5-22). Therefore, the rationale to support a conclusion that the claim would have been obvious is that the combining prior art elements according to known methods to yield predictable results to one of ordinary skill in the art. See MPEP § 2143(I)(A).
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure:
Martina et al. (“Learning the noise fingerprint of quantum devices,” 23 September 2021, https://arxiv.org/abs/2109.11405) disclosing machine learning techniques to classify quantum noise
Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
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/Ryan Barrett/
Primary Examiner, Art Unit 2148
Prosecution Insights