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Scalable quantum information processing with integrated photonics requires quantum logic operations with high fidelity and robustness. Directional couplers, the fundamental elements enabling quantum interference and logic operations, are…

Generations of technologies with fundamentally new information processing capabilities will emerge if microscopic physical systems can be controlled to encode, transmit, and process quantum information, at scale and with high fidelity. In…

Quantum Physics · Physics 2020-05-06 Jianwei Wang , Fabio Sciarrino , Anthony Laing , Mark G. Thompson

Integrated photonic circuits have a strong potential to perform quantum information processing. Indeed, the ability to manipulate quantum states of light by integrated devices may open new perspectives both for fundamental tests of quantum…

Classification using variational quantum circuits is a promising frontier in quantum machine learning. Quantum supervised learning (QSL) applied to classical data using variational quantum circuits involves embedding the data into a quantum…

Quantum Physics · Physics 2026-03-16 Yujin Kim , Changjae Im , Taehyun Kim , Tak Hur , Daniel K. Park

Variational quantum algorithms hold great promise for unlocking the power of near-term quantum processors, yet high measurement costs, barren plateaus, and challenging optimization landscapes frequently hinder them. Here, we introduce…

Quantum Physics · Physics 2026-03-10 Mengzhen Ren , Yu-Cheng Chen , Yangsen Ye , Min-Hsiu Hsieh , Alice Hu , Chang-Yu Hsieh

The goal of integrated quantum photonics is to combine components for the generation, manipulation, and detection of non-classical light in a phase stable and efficient platform. Solid-state quantum emitters have recently reached…

Applied Physics · Physics 2020-04-07 Je-Hyung Kim , Shahriar Aghaeimeibodi , Jacques Carolan , Dirk Englund , Edo Waks

Quantum machine learning algorithms have very recently attracted significant attention in photonic platforms. In particular, reconfigurable integrated photonic circuits offer a promising route, thanks to the possibility of implementing…

Variational quantum algorithms (VQAs), as one of the most promising routes in the noisy intermediate-scale quantum (NISQ) era, offer various potential applications while also confront severe challenges due to near-term quantum hardware…

Quantum Physics · Physics 2024-12-12 Shi-Xin Zhang , Jiaqi Miao , Chang-Yu Hsieh

Advances in quantum technologies are accelerating the demand for optical quantum state sensors that combine high precision, versatility, and scalability within a unified hardware platform. Quantum reservoir computing offers a powerful route…

Photons are a ubiquitous carrier of quantum information: they are fast, suffer minimal decoherence, and do not require huge cryogenic facilities. Nevertheless, their intrinsically weak photon-photon interactions remain a key obstacle to…

Parameterized quantum circuits (PQCs) play an essential role in the application of variational quantum algorithms (VQAs) in noisy intermediate-scale quantum (NISQ) devices. The PQCs are a leading candidate to achieve a quantum advantage in…

Quantum Physics · Physics 2025-10-10 Joona V. Pankkonen , Matti Raasakka , Andrea Marchesin , Ilkka Tittonen

We show how techniques from machine learning and optimization can be used to find circuits of photonic quantum computers that perform a desired transformation between input and output states. In the simplest case of a single input state,…

We present a systematic study of how quantum circuit design, specifically the depth of the variational ansatz and the choice of quantum feature mapping, affects the performance of hybrid quantum-classical neural networks on a causal…

Quantum Physics · Physics 2026-02-10 Silvie Illésová , Tomasz Rybotycki , Piotr Gawron , Martin Beseda

Despite extensive research efforts, few quantum algorithms for classical optimization demonstrate realizable quantum advantage. The utility of many quantum algorithms is limited by high requisite circuit depth and nonconvex optimization…

Quantum Physics · Physics 2022-01-27 Taylor L. Patti , Jean Kossaifi , Anima Anandkumar , Susanne F. Yelin

We introduce a variational quantum computing approach for quantum state reconstruction within a discretized logical framework, using experimental measurement data as input. By mapping the reconstruction cost function onto an Ising model,…

Quantum Physics · Physics 2026-04-03 Mwezi Koni , Shawal Kassim , Paola C. Obando , Neelan Gounden , Isaac Nape

Programmable photonic integrated circuits represent an emerging technology that amalgamates photonics and electronics, paving the way for light-based information processing at high speeds and low power consumption. Considering their wide…

Optics · Physics 2025-02-25 Matthew Markowitz , Kevin Zelaya , Mohammad-Ali Miri

Quantum error correction is vital for implementing universal quantum computing. A key component is the encoding circuit that maps a product state of physical qubits into the encoded multipartite entangled logical state. Known methods are…

Quantum Physics · Physics 2021-04-07 Xiaosi Xu , Simon C. Benjamin , Xiao Yuan

Variational Quantum Algorithms are among the most promising systems to implement quantum computing under the Noisy-Intermediate Scale Quantum (NISQ) technology. In variational quantum algorithm, wavefunction represented by a parametrized…

Quantum Physics · Physics 2023-01-02 H. Davoodi Yeganeh

The parameters of a quantum system grow exponentially with the number of involved quantum particles. Hence, the associated memory requirement goes well beyond the limit of best classic computers for quantum systems composed of a few dozen…

Quantum Physics · Physics 2021-08-31 Jakob S. Kottmann , Mario Krenn , Thi Ha Kyaw , Sumner Alperin-Lea , Alán Aspuru-Guzik

High-dimensional quantum entanglement is an important resource for emerging quantum technologies such as quantum communication and quantum computation. The scalability of metres-long experimental setups limits high-dimensional entanglement…

Quantum Physics · Physics 2024-09-06 Tavshabad Kaur , Daniel Peace , Jacquiline Romero