Quantum Compilation for NISQ-Era Quantum Computers

Contacts:


Fereshte MozafariPhD student, EPFL-IC-LSI

Mathias SoekenPost-doc, EPFL-IC-LSI 

Giovanni De Micheli, Professor, EPFL-IC-LSI

Introduction:

With the release of quantum computers comprising of 72 and 50 qubits by Google and IBM, respectively, and with achieving of “quantum supremacy” by Google, it is reasonable to expect to have quantum computers including hundreds of qubits in the near future. This upcoming period is termed Noisy Intermediate Scale Quantum (NISQ) era, because of the noisy characteristics of near-term devices.

Computation on a NISQ hardware is modeled using a library of supported quantum gates which can be directly implemented on it and a coupling graph that specifies available qubit interactions for multi-qubit quantum gates.

While improvements to NISQ hardware are continuously being made by experimentalists, quantum computing experts can contribute to the utility of NISQ devices by developing software. This software would aim to adapt textbook quantum algorithms (e.g., for factoring or quantum simulation) to NISQ constraints, that include: (1) limited number of qubits, (2) limited connectivity between qubits, (3) limited hardware-specific gate sets, and (4) limited circuit depth due to noise. Algorithms adapted to these constraints will likely look dramatically different from their textbook counterparts. Such software, that performs the task of translating quantum algorithms into quantum circuits according to NISQ constraints, is called a quantum compiler.

Quantum algorithms assume some specific initial state in superposition before performing the desired application-specific computations. The preparation of such states itself requires a computation performed by a quantum circuit. Moreover, some quantum computing applications (e.g., quantum machine learning, and quantum chemistry) require to efficiently load large sets of classical data into quantum states. As a result, quantum state preparation is an important quantum compilation task.

Goal:

During my Ph.D. studies, my goal is to develop efficient and effective compilation algorithms that can be used to help quantum computing applications.

Main publications available here.