activity
20242026
collaborators

20 papers

physics.chem-ph2026

Quantum phases in endofullerene zigzag chains

Tobias Serwatka, Muhammad Shaeer Moeed, Roger G. Melko +1

We employ large-scale density matrix renormalization group calculations to study the quantum phases of dipolar molecules confined in bent (zigzag) endofullerene chains, as a functi…

quant-ph2026

Diffusion-warm sampling of the XY model enables fast thermalization at scale

Sehmimul Hoque, Roger Melko, Pooya Ronagh

We introduce a novel technique for scalable sampling of spin-system states with continuous symmetries using diffusion models. By applying our approach to the XY model, a fundamenta…

cond-mat.quant-gas2026

Superfluidity in the spin-1/2 XY model with power-law interactions

Muhammad Shaeer Moeed, Costanza Pennaforti, Adrian Del Maestro +1

In trapped-ion quantum simulators, effective spin-1/2 XY interactions can be engineered via laser-induced coupling between internal atomic states and collective phonon modes. In th…

quant-ph2026

Distributions of Noisy Expectation Values over Sets of Measurement Operators

Matthew Duschenes, Roger G. Melko, Juan Carrasquilla +1

Expectation values of measurement operators, interpreted as measurement probabilities, arise frequently throughout quantum algorithms. When quantum states are randomly distributed,…

cond-mat.dis-nn2026

Unlearnable phases of matter

Tarun Advaith Kumar, Yijian Zou, Amir-Reza Negari +2

We identify fundamental limitations in machine learning by demonstrating that non-trivial mixed-state phases of matter are computationally hard to learn. Focusing on unsupervised l…

cs.LG2026

Private and interpretable clinical prediction with quantum-inspired tensor train models

José Ramón Pareja Monturiol, Juliette Sinnott, Roger G. Melko +1

Machine learning in clinical settings must balance predictive accuracy, interpretability, and privacy. Models such as logistic regression (LR) offer transparency, while neural netw…