collaborators

6 papers

quant-ph2026

Low Latency GNN Accelerator for Quantum Error Correction

Alessio Cicero, Luigi Altamura, Moritz Lange +2

Quantum computers can solve selected problems more efficiently than classical computers, but current devices are limited by high physical error rates. Quantum Error Correction (QEC…

quant-ph2026

Comparing and learning figures of merit for quantum circuit compilation

Harshdeep Singh, Marvin Richter, Mats Granath +1

To make quantum algorithms executable on a particular quantum device, they need to be compiled into circuits that respect constraints of the quantum hardware. This compilation usua…

quant-ph2026

Bias-Preserving Gates and Quantum Error Correction With Dual-Rail Cat Codes

Debjyoti Biswas, Nikhil Sharma, Alberto Salvador +4

Scalable fault-tolerant quantum computation requires quantum error-correcting codes that simultaneously support universal logical operations, suppress hardware-specific noise, and…

cs.LG2026

Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks

Longde Huang, Oleksandr Balabanov, Hampus Linander +3

Equivariant network architectures are a well-established tool for predicting invariant or equivariant quantities. However, almost all learning problems considered in this context f…

quant-ph2026

Multiple-time Quantum Imaginary Time Evolution

Julio Del Castillo, Mats Granath, Evert van Nieuwenburg

Quantum Imaginary-Time Evolution (QITE) is a powerful method for preparing ground states on quantum hardware. However, executing QITE has costly measurement budgets for general Ham…

quant-ph2025

Quantum computing and artificial intelligence: status and perspectives

Giovanni Acampora, Andris Ambainis, Natalia Ares +36

This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could supp…