Kanqas: Kolmogorov-arnold network for quantum architecture search
Quantum architecture Search (QAS) is a promising direction for optimization and automated
design of quantum circuits towards quantum advantage. Recent techniques in QAS …
design of quantum circuits towards quantum advantage. Recent techniques in QAS …
Quantum circuit synthesis and compilation optimization: Overview and prospects
Quantum computing is regarded as a promising paradigm that may overcome the current
computational power bottlenecks in the post-Moore era. The increasing maturity of quantum …
computational power bottlenecks in the post-Moore era. The increasing maturity of quantum …
A quantum information theoretic analysis of reinforcement learning-assisted quantum architecture search
In the field of quantum computing, variational quantum algorithms (VQAs) represent a pivotal
category of quantum solutions across a broad spectrum of applications. These algorithms …
category of quantum solutions across a broad spectrum of applications. These algorithms …
YAQQ: Yet Another Quantum Quantizer--Design Space Exploration of Quantum Gate Sets using Novelty Search
In the standard circuit model of quantum computation, the number and quality of the
quantum gates composing the circuit influence the runtime and fidelity of the computation …
quantum gates composing the circuit influence the runtime and fidelity of the computation …
Enhancing quantum memory lifetime with measurement-free local error correction and reinforcement learning
Reliable quantum computation requires systematic identification and correction of errors that
occur and accumulate in quantum hardware. To diagnose and correct such errors, standard …
occur and accumulate in quantum hardware. To diagnose and correct such errors, standard …
Reinforcement learning-assisted quantum architecture search for variational quantum algorithms
A Kundu - arxiv preprint arxiv:2402.13754, 2024 - arxiv.org
A significant hurdle in the noisy intermediate-scale quantum (NISQ) era is identifying
functional quantum circuits. These circuits must also adhere to the constraints imposed by …
functional quantum circuits. These circuits must also adhere to the constraints imposed by …
Trainability maximization using estimation of distribution algorithms assisted by surrogate modelling for quantum architecture search
Quantum architecture search (QAS) involves optimizing both the quantum parametric circuit
configuration but also its parameters for a variational quantum algorithm. Thus, the problem …
configuration but also its parameters for a variational quantum algorithm. Thus, the problem …
Quantum metric learning with fuzzy-informed learning
C Huang, S Zhang, Y Chang, L Yan - Physica A: Statistical Mechanics and …, 2024 - Elsevier
By constructing a quantum circuit with adjustable parameters, variational quantum circuits
are capable of embedding input data into Hilbert space and facilitating the execution of …
are capable of embedding input data into Hilbert space and facilitating the execution of …
Improving thermal state preparation of Sachdev-Ye-Kitaev model with reinforcement learning on quantum hardware
A Kundu - arxiv preprint arxiv:2501.11454, 2025 - arxiv.org
The Sachdev-Ye-Kitaev (SYK) model, known for its strong quantum correlations and chaotic
behavior, serves as a key platform for quantum gravity studies. However, variationally …
behavior, serves as a key platform for quantum gravity studies. However, variationally …
Hybrid Classical-Quantum architecture for vectorised image classification of hand-written sketches
Quantum machine learning (QML) investigates how quantum phenomena can be exploited
in order to learn data in an alternative way,\textit {eg} by means of a quantum computer …
in order to learn data in an alternative way,\textit {eg} by means of a quantum computer …