From the 1 of 6 linked papers with an AI index.
6 papers
Analytic correspondence between multipartite entanglement and quantum phase transitions
Huynh Le Dan Linh, Vu Tuan Hai, Le Bin Ho
We derive an analytic correspondence between multipartite concentratable entanglement (CE) and quantum phase transitions in one-dimensional quantum spin systems. We prove that CE s…
Benchmarking loss functions for trainable quantum feature maps
Nguyen Dinh Quyen, Vu Tuan Hai, Quoc Chuong Nguyen +2
The paper evaluates how different loss functions affect the training of quantum feature maps used in quantum machine learning, finding that Log-Likelihood Loss offers stable optimi…
Towards Automated Selection of Quantum Encoding Circuits via Meta-Learning
Dao Duy Tung, Nguyen Quoc Chuong, Vu Tuan Hai +2
In recent years, quantum kernel methods have shown promising applications on near-term quantum devices. However, selecting an appropriate encoding circuit for a given dataset requi…
Exact gradient for general cost functions in variational quantum algorithms
Jesus Urbaneja, Le Bin Ho
We present a unitary-based gradient formulation for variational quantum algorithms (VQAs) that applies to general differentiable cost function defined by a parameterized quantum ci…
Advancing quantum process tomography through quantum compilation
Huynh Le Dan Linh, Vu Tuan Hai, Le Bin Ho
Quantum process tomography (QPT) plays a central role in characterizing quantum gates and circuits, diagnosing quantum devices, calibrating hardware, and supporting quantum error c…
Statistical analysis of barren plateaus in variational quantum algorithms
Le Bin Ho, Jesus Urbaneja, Sahel Ashhab
We investigate the barren plateau (BP) phenomenon in variational quantum algorithms using a statistical approach. Using Gaussian function models, we identify three distinct types o…