Quantum computing aims at faster computations by using superposition and entanglement of qubits. This could revolutionize entire industries – from pharmaceuticals and materials science to finance and logistics. Yet the promise of quantum computing is still limited by today’s hardware. Current devices operate in the so-called NISQ era (Noisy Intermediate-Scale Quantum), where qubits are scarce, error-prone, and difficult to control. Fault-tolerant quantum computing requires quantum error correction, whose scalability is currently limited. Quantum software plays a critical role in practical quantum computing, to bridge the gap from applications to hardware.
“Quantum Software” refers to programs running on quantum computers and to the design-automation tools to construct such quantum programs. Research on quantum software investigates high-level quantum programming languages, compiler techniques, and algorithms for automated synthesis, optimization, verification, and simulation of quantum programs. Together, these techniques support a long-term vision of building a quantum software stack that bridges the gap between high-level quantum algorithms and low-level circuits.
Quantum algorithms are often described at a high level, but to run them on hardware, they must be compiled into quantum circuits. These circuits specify the exact operations performed on qubits. However, the translation from algorithms to circuits is rarely efficient: the resulting circuits are often far larger and noisier than necessary. Each extra operation increases noise and reduces reliability. Quantum circuit optimization – finding smaller, faster, and less noisy equivalents of a given circuit – is therefore one of the key challenges for enabling near-term real-world quantum applications. Optimized circuits not only increase accuracy on today’s noisy machines but also reduce the costly overhead of quantum error correction, which is needed for future, fault-tolerant quantum computers.
We explore efficient implementations of quantum error correction codes, an essential step toward scaling quantum computing from today’s noisy devices to fully fault-tolerant quantum computers.
QoptiQ develops algorithms that go beyond the rough shortcuts used in today’s quantum compilers. We aim for circuits that are mathematically proven to be optimal for gate count and circuit depth, also handling hardware-specific connectivity constraints.
We use Satisfiability Solving and Automated Planning to synthesize optimal layout-aware quantum circuits, focusing on minimizing the number of the 2-qubit CNOT gates and circuit depth.
Find us on Github: https://github.com/Quantum-Software-Aarhus
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