Quantum-assisted quantum compiling
Compiling quantum algorithms for near-term quantum computers (accounting for connectivity and native gate alphabets) is a major challenge that has received significant attention both by industry and academia. Avoiding the exponential overhead of classical simulation of quantum dynamics will allow co...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2019-05-01
|
| Series: | Quantum |
| Online Access: | https://quantum-journal.org/papers/q-2019-05-13-140/pdf/ |
| _version_ | 1818015841746157568 |
|---|---|
| author | Sumeet Khatri Ryan LaRose Alexander Poremba Lukasz Cincio Andrew T. Sornborger Patrick J. Coles |
| author_facet | Sumeet Khatri Ryan LaRose Alexander Poremba Lukasz Cincio Andrew T. Sornborger Patrick J. Coles |
| author_sort | Sumeet Khatri |
| collection | DOAJ |
| description | Compiling quantum algorithms for near-term quantum computers (accounting for connectivity and native gate alphabets) is a major challenge that has received significant attention both by industry and academia. Avoiding the exponential overhead of classical simulation of quantum dynamics will allow compilation of larger algorithms, and a strategy for this is to evaluate an algorithm's cost on a quantum computer. To this end, we propose a variational hybrid quantum-classical algorithm called quantum-assisted quantum compiling (QAQC). In QAQC, we use the overlap between a target unitary $U$ and a trainable unitary $V$ as the cost function to be evaluated on the quantum computer. More precisely, to ensure that QAQC scales well with problem size, our cost involves not only the global overlap ${\rm Tr}(V^†U)$ but also the local overlaps with respect to individual qubits. We introduce novel short-depth quantum circuits to quantify the terms in our cost function, and we prove that our cost cannot be efficiently approximated with a classical algorithm under reasonable complexity assumptions. We present both gradient-free and gradient-based approaches to minimizing this cost. As a demonstration of QAQC, we compile various one-qubit gates on IBM's and Rigetti's quantum computers into their respective native gate alphabets. Furthermore, we successfully simulate QAQC up to a problem size of 9 qubits, and these simulations highlight both the scalability of our cost function as well as the noise resilience of QAQC. Future applications of QAQC include algorithm depth compression, black-box compiling, noise mitigation, and benchmarking. |
| first_indexed | 2024-04-14T07:03:05Z |
| format | Article |
| id | doaj.art-fb52be12dd6d4173b22fe864366efcc0 |
| institution | Directory Open Access Journal |
| issn | 2521-327X |
| language | English |
| last_indexed | 2024-04-14T07:03:05Z |
| publishDate | 2019-05-01 |
| publisher | Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften |
| record_format | Article |
| series | Quantum |
| spelling | doaj.art-fb52be12dd6d4173b22fe864366efcc02022-12-22T02:06:41ZengVerein zur Förderung des Open Access Publizierens in den QuantenwissenschaftenQuantum2521-327X2019-05-01314010.22331/q-2019-05-13-14010.22331/q-2019-05-13-140Quantum-assisted quantum compilingSumeet KhatriRyan LaRoseAlexander PorembaLukasz CincioAndrew T. SornborgerPatrick J. ColesCompiling quantum algorithms for near-term quantum computers (accounting for connectivity and native gate alphabets) is a major challenge that has received significant attention both by industry and academia. Avoiding the exponential overhead of classical simulation of quantum dynamics will allow compilation of larger algorithms, and a strategy for this is to evaluate an algorithm's cost on a quantum computer. To this end, we propose a variational hybrid quantum-classical algorithm called quantum-assisted quantum compiling (QAQC). In QAQC, we use the overlap between a target unitary $U$ and a trainable unitary $V$ as the cost function to be evaluated on the quantum computer. More precisely, to ensure that QAQC scales well with problem size, our cost involves not only the global overlap ${\rm Tr}(V^†U)$ but also the local overlaps with respect to individual qubits. We introduce novel short-depth quantum circuits to quantify the terms in our cost function, and we prove that our cost cannot be efficiently approximated with a classical algorithm under reasonable complexity assumptions. We present both gradient-free and gradient-based approaches to minimizing this cost. As a demonstration of QAQC, we compile various one-qubit gates on IBM's and Rigetti's quantum computers into their respective native gate alphabets. Furthermore, we successfully simulate QAQC up to a problem size of 9 qubits, and these simulations highlight both the scalability of our cost function as well as the noise resilience of QAQC. Future applications of QAQC include algorithm depth compression, black-box compiling, noise mitigation, and benchmarking.https://quantum-journal.org/papers/q-2019-05-13-140/pdf/ |
| spellingShingle | Sumeet Khatri Ryan LaRose Alexander Poremba Lukasz Cincio Andrew T. Sornborger Patrick J. Coles Quantum-assisted quantum compiling Quantum |
| title | Quantum-assisted quantum compiling |
| title_full | Quantum-assisted quantum compiling |
| title_fullStr | Quantum-assisted quantum compiling |
| title_full_unstemmed | Quantum-assisted quantum compiling |
| title_short | Quantum-assisted quantum compiling |
| title_sort | quantum assisted quantum compiling |
| url | https://quantum-journal.org/papers/q-2019-05-13-140/pdf/ |
| work_keys_str_mv | AT sumeetkhatri quantumassistedquantumcompiling AT ryanlarose quantumassistedquantumcompiling AT alexanderporemba quantumassistedquantumcompiling AT lukaszcincio quantumassistedquantumcompiling AT andrewtsornborger quantumassistedquantumcompiling AT patrickjcoles quantumassistedquantumcompiling |