11 citations · 32 across the 8 of their papers we have counts for
8 papers
Unlocking Multidimensional Integration with Quantum Adaptive Importance Sampling
Konstantinos Pyretzidis, Jorge J. Martínez de Lejarza, Germán Rodrigo
Multidimensional numerical integration is a central ingredient of theoretical predictions in high-energy physics, where multiloop Feynman diagrams and phase-space integrals are com…
Quantum Chebyshev Probabilistic Models for Fragmentation Functions
Jorge J. Martínez de Lejarza, Hsin-Yu Wu, Oleksandr Kyriienko +2
Quantum generative modeling is emerging as a powerful tool for advancing data analysis in high-energy physics, where complex multivariate distributions are common. However, efficie…
Quantum integration of decay rates at second order in perturbation theory
Jorge J. Martínez de Lejarza, David F. Rentería-Estrada, Michele Grossi +1
We present the first quantum computation of a total decay rate in high-energy physics at second order in perturbative quantum field theory. This work underscores the confluence of…
Vacuum amplitudes and time-like causal unitary in the loop-tree duality
The LTD Collaboration, Selomit Ramírez-Uribe, Andrés E. Rentería-Olivo +8
We present the first proof-of-concept application to decay processes at higher perturbative orders of LTD causal unitary, a novel methodology that exploits the causal properties of…
Loop Feynman integration on a quantum computer
Jorge J. Martínez de Lejarza, Leandro Cieri, Michele Grossi +2
This work investigates in detail the performance and advantages of a new quantum Monte Carlo integrator, dubbed Quantum Fourier Iterative Amplitude Estimation (QFIAE), to numerical…
Quantum Fourier Iterative Amplitude Estimation
Jorge J. Martínez de Lejarza, Michele Grossi, Leandro Cieri +1
Monte Carlo integration is a widely used numerical method for approximating integrals, which is often computationally expensive. In recent years, quantum computing has shown promis…
Quantum jet clustering with LHC simulated data
Jorge J. Martínez de Lejarza, Leandro Cieri, Germán Rodrigo
We study the case where quantum computing could improve jet clustering by considering two new quantum algorithms that might speed up classical jet clustering algorithms. The first…
Quantum clustering and jet reconstruction at the LHC
Jorge J. Martínez de Lejarza, Leandro Cieri, Germán Rodrigo
Clustering is one of the most frequent problems in many domains, in particular, in particle physics where jet reconstruction is central in experimental analyses. Jet clustering at…