Short-depth active learning quantum amplitude estimation without eigenstate collapse
Techniques and a system to facilitate estimation of a quantum phase, and more specifically, to facilitate estimation of an expectation value of a quantum state, by utilizing a hybrid of quantum and classical methods are provided. In one example, a system is provided. The system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can include an encoding component and a learning component. The encoding component can encode an expectation value associated with a quantum state. The learning component can utilize stochastic inference to determine the expectation value based on an uncollapsed eigenvalue pair.
1. A system, comprising:
a memory that stores computer executable components, and
a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a learning component that utilizes stochastic inference to determine an expectation value during a first time interval based on an uncollapsed eigenvalue pair retrieved by an active learning process, wherein the first time interval is less than a second time interval where the uncollapsed eigenvalue pair is retrieved without use of the active learning process; and
an encoding component that encodes the expectation value associated with a quantum state.
2. The system of claim 1 , further comprising a quantum processor, wherein the encoding component encodes the expectation value as a phase, wherein the encoding component is operatively coupled to the quantum processor.
3. The system of claim 1 , wherein the stochastic inference comprises Bayesian learning of an eigenvalue corresponding to the uncollapsed eigenvalue pair.
4. The system of claim 1 , wherein the encoding component encodes the expectation value based on an amplitude of the expectation value.
5. The system of claim 1 , wherein the learning component comprises a measuring component that utilizes a first ancilla qubit to retrieve the uncollapsed eigenvalue pair.
6. The system of claim 5 , wherein the measuring component further utilizes a second ancilla qubit to retrieve the uncollapsed eigenvalue pair, and wherein the learning component utilizes the stochastic inference to determine the expectation value further based on the uncollapsed eigenvalue pair retrieved by the second ancilla qubit.
7. The system of claim 5 , wherein the measuring component produces an output comprising a probabilistic measurement based on at least one ancilla qubit.
8. A computer-implemented method, comprising:
determining, by a system operatively coupled to a processor and memory, utilizing stochastic inference, an expectation value during a first time interval based on an uncollapsed eigenvalue pair retrieved by an active learning process, wherein the first time interval is less than a second time interval where the uncollapsed eigenvalue pair is retrieved without use of the active learning process; and
encoding, by the system, the expectation value associated with a quantum state.
9. The computer-implemented method of claim 8 , wherein the encoding comprises encoding the expectation value as a phase.
10. The computer-implemented method of claim 8 , wherein the stochastic inference comprises Bayesian learning of an eigenvalue corresponding to the uncollapsed eigenvalue pair.
11. The computer-implemented method of claim 8 , wherein the encoding comprises encoding the expectation value based on an amplitude of the expectation value.
12. The computer-implemented method of claim 8 , further comprising utilizing, by the system, a first ancilla qubit to retrieve the uncollapsed eigenvalue pair.
13. The computer-implemented method of claim 12 , further comprising utilizing, by the system, a second ancilla qubit to retrieve the uncollapsed eigenvalue pair, and wherein the determining the expectation value is further based on the uncollapsed eigenvalue pair retrieved by the second ancilla qubit.
14. The computer-implemented method of claim 12 , further comprising producing, by the system, an output comprising a probabilistic measurement based on at least one ancilla qubit.
15. A computer program product for quantum state estimation, the computer program product comprising a non-transitory computer readable medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
determine, utilizing stochastic inference, an expectation value during a first time interval based on an uncollapsed eigenvalue pair retrieved by an active learning process, wherein the first time interval is less than a second time interval where the uncollapsed eigenvalue pair is retrieved without use of the active learning process; and
encode the expectation value associated with a quantum state.
16. The computer program product of claim 15 , wherein the expectation value is encoded as a phase.
17. The computer program product of claim 15 , wherein the stochastic inference comprises Bayesian learning of an eigenvalue corresponding to the uncollapsed eigenvalue pair.
18. The computer program product of claim 15 , wherein the expectation value is encoded based on an amplitude of the expectation value.
19. The computer program product of claim 15 , wherein the program instructions are further executable by the processor to cause the processor to:
utilize a first ancilla qubit to retrieve the uncollapsed eigenvalue pair.
20. The computer program product of claim 15 , wherein the program instructions are further executable by the processor to cause the processor to:
utilize a second ancilla qubit to retrieve the uncollapsed eigenvalue pair, and wherein the expectation value is determined further based on the uncollapsed eigenvalue pair retrieved by the second ancilla qubit.
21. The computer program product of claim 15 , wherein the program instructions are further executable by the processor to cause the processor to:
produce an output comprising a probabilistic measurement based on at least one ancilla qubit.
22. A system comprising:
a memory that stores computer executable components, and
a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a measuring component that utilizes a first ancilla qubit and a second ancilla qubit to retrieve an uncollapsed eigenvalue pair;
a learning component that utilizes stochastic inference to determine an expectation value based on the uncollapsed eigenvalue pair retrieved by the first ancilla qubit and the second ancilla qubit; and
an encoding component that encodes the expectation value associated with a quantum state.
23. The system of claim 22 , wherein the measuring component produces an output comprising a probabilistic measurement based on at least one ancilla qubit.
24. A computer-implemented method, comprising:
utilizing, by a system operatively coupled to a processor and memory, a first ancilla qubit and a second ancilla qubit to retrieve an uncollapsed eigenvalue pair;
utilizing, by the system, stochastic inference to determine an expectation value based on the uncollapsed eigenvalue pair retrieved by the first ancilla qubit and the second ancilla qubit; and
encoding, by the system, the expectation value associated with a quantum state.
25. The computer-implemented method of claim 24 , producing an output comprising a probabilistic measurement based on at least one ancilla qubit.