A limited number of qubits, high error rates, and limited qubit connectivity are major challenges for effective near-term quantum computations. Quantum circuit partitioning divides a quantum computation into classical postprocessing steps and a set of smaller scale quantum computations that individually require fewer qubits, lower qubit connectivity, and typically incur less error. However, as partitioning […]
Noisy intermediate-scale quantum algorithms, which run on noisy quantum computers, should be carefully designed to boost the output state fidelity. While several compilation approaches have been proposed to minimize circuit errors, they often omit the detailed circuit structure information that does not affect the circuit depth or the gate count. In the presence of spatial […]
In the noisy intermediate-scale quantum (NISQ) era, the idea of quantum multiprogramming , running multiple quantum circuits (QCs) simultaneously on the same hardware, helps to improve the throughput of quantum computation. However, the crosstalk, unwanted interference between qubits on NISQ processors, may cause performance degradation when using multiprogramming. To address this challenge, we introduce palloq […]
Research on near-term quantum machine learning has explored how classical machine learning algorithms endowed with access to quantum kernels (similarity measures) can outperform their purely classical counterparts. Although theoretical work has shown a provable advantage on synthetic data sets, no work done to date has studied empirically whether the quantum advantage is attainable and with […]
We seek to develop better upper bound guarantees on the depth of quantum CZ gate, cnot gate, and Clifford circuits than those reported previously. We focus on the number of qubits n≤ 1 345 000 (de Brugière et al. , 2021), which represents the most practical use case. Our upper bound on the depth of CZ circuits is ⌊n/2+0.4993⋅log2(n)+3.0191⋅log(n)−10.9139⌋ , improving the best-known […]
As quantum computing is still in its infancy, there is an inherent lack of knowledge and technology to test a quantum program properly. In the classical realm, mutation testing has been successfully used to evaluate how well a program’s test suite detects seeded faults (i.e., mutants). In this article, building on the definition of syntactically […]
One of the major obstacles to the adoption of quantum computing is the requirement to define quantum circuits at the quantum gate level. Many programmers are familiar with high-level or low-level programming languages but not quantum gates nor the low-level quantum logic required to derive useful results from quantum computers. The steep learning curve involved […]
Hybrid quantum-classical algorithms, such as variational quantum algorithms (VQAs), are suitable for implementation on noisy intermediate-scale quantum computers. In this article, we expand an implicit step of VQAs: the classical precomputation subroutine, which can nontrivially use classical algorithms to simplify, transform, or specify problem instance-specific variational quantum circuits. In VQA, there is a tradeoff between […]
As each quantum algorithm requires a specific initial quantum state, quantum state preparation is an important task in quantum computing. The preparation of quantum states is performed by a quantum circuit consisting of controlled-NOT (CNOT) and single-qubit gates. Known algorithms to prepare arbitrary n -qubit quantum states create quantum circuits in O(2n) runtime and use O(2n) CNOTs, which are more expensive […]
As quantum network technologies develop, the need for teaching and engineering tools such as simulators and emulators rises. QuNetSim addresses this need. QuNetSim is a Python software framework that delivers an easy-to-use interface for simulating quantum networks at the network layer, which can be extended at little effort of the user to implement the corresponding […]