We present 1P1Q, a novel quantum data encoding approach tailored specifically for particle physics, where each particle in collision events is mapped onto an individual qubit. This method bypasses classical data compression, enabling direct and lossless representation of event-level kinematic details on quantum devices. We showcase the effectiveness of 1P1Q in two key quantum machine learning...
Monte Carlo integration lies at the heart of theoretical predictions in high-energy physics (HEP), underpinning the simulation of scattering processes at facilities like the Large Hadron Collider. However, as the complexity of target processes grows, classical methods rapidly become computationally demanding, consuming billions of CPU hours annually. In this talk, I will present a...
Perturbative Quantum Field Theory is central to perform accurate theoretical predictions of observables at high-energy colliders. Fundamental concepts in this framework, such as loop Feynman diagrams and the phase-space, involve evaluating multidimensional integrals that are computationally intensive due to divergences and complex mathematical structures. To address these challenges and...
Transition Edge Sensors (TES) are widely employed in the field of quantum sensing due to their exceptional energy resolution and sensitivity to single quanta of energy. When operated in its superconducting transition at mK temperatures, a single photon absorbed by the TES produces a significant change in its resistance, generating a measurable signal. In particular, TESs are an ideal tool for...
The realm of particle physics is full of astonishing phenomena and open problems. One is confinement, typical of QCD in (3+1)D with SU(3) gauge group. Lattice Gauge Theory (LGT) enables us to study it numerically with Tensor Networks. We focus on the pure Z₂ LGT in (2+1)D, dual to the quantum Ising model, which preserves criticality while reducing degrees of freedom. Our numerical...
In the high-luminosity era of particle physics, advanced computing methods are vital for tackling the unprecedented scale and complexity of data, inspiring us to explore innovative quantum approaches for data analysis. We investigate the impact of incorporating problem-specific permutation invariance into hardware-efficient quantum fidelity kernels for high energy physics data analysis in...
Parton distribution functions (PDFs) describe universal properties of hadrons. They provide insights into the non-perturbative internal structure of bound states and are highly significant for experiments. Calculating PDFs involves evaluating matrix elements with a Wilson line in a light-cone direction. This poses significant challenges for Monte Carlo methods in Euclidean formulation of...
A promising way to probe physics beyond the Standard Model is to
search for gravitational wave (GW) signals at high frequencies where
known astrophysical sources can not obscure the signal. Similar to the
search for dark matter, microwave cavity resonators can be used to
detect faint effects from GWs. We will report on the progress of our project to operate such a detector and highlight...
While perturbative methods have led to significant insights into fundamental interactions,non-perturbative phenomena remain poorly understood—particularly in regimes where Monte Carlo (MC) techniques suffer from the sign problem, such as in dense nuclear matter and real-time dynamics in Quantum Chromodynamics (QCD). Tensor Network (TN) methods, which are not affected by the sign...
We propose a quantum protocol for efficiently learning and sampling multivariate probability distributions that commonly appear in high-energy physics. Our approach introduces a bivariate probabilistic model based on generalized Chebyshev polynomials, which is (pre-)trained as an explicit circuit-based model for two correlated variables, and sampled efficiently with the use of quantum...
Reconstructing the trajectories of charged particles as they traverse several detector layers is a key ingredient for event reconstruction at LHC and virtually any particle physics experiment. The limited bandwidth available, together with the high rate of tracks per second O(10^10) - where each track consists of a variable number of measurements - makes this problem exceptionally challenging...
Diffusion models have recently emerged as powerful generative tools, capable of learning and synthesizing high-dimensional data distributions. In high-energy physics (HEP), these models provide an innovative route to address complex inverse problems—most notably, reconstructing the true particle-level signals from detector-smeared measurements. Traditional unfolding methods, which attempt to...
Quantum-based generative models offer an alternative route for simulating intricate phenomena in high-energy physics. One notable example is the simulation of calorimeter showers, which involve highly stochastic and high-dimensional data crucial for determining particle types and reconstructing energy in experiments such as those conducted at the LHC. As the complexity and scale of these...
Quantum noise poses a fundamental limitation to the sensitivity of second-generation terrestrial gravitational wave (GW) detectors,affecting both low and high frequencies through radiation pressure noise and shot noise, respectively. Overcomming this limitation is crucial for the improvement of the detector’s sensitivities. For this reason all international collaborations have undertaken an...
In the context of the ECFA detector roadmap, several collaborations have been formed with a view towards carrying out the necessary detector R&D for future particle physics experiments. Among these, the DRD5 collaboration focuses on R&D on quantum sensors and related topics, specifically working along five technological axes (Quantum systems in traps and beams; Low-dimensional quantum...
Modern experiments in particle, astroparticle physics, and cosmology, particularly those probing for New Physics, are increasingly relying on quantum sensors to achieve unprecedented sensitivities. These include efforts to determine the absolute neutrino mass scale, search for neutrinoless double beta decay, detect potential dark matter candidates, or measure the B-mode polarization of the...
The exceptionally low-lying isomer thorium-229m, which had been observed via radioactive decay, was the subject of intense research for several decades due to its potential as a nuclear clock state. Recently, this state was laser-excited for the first time, bringing us an important step closer to the realisation of nuclear clocks, but also opening up new possibilities to search for new physics...
Scattering processes in gauge theories are fundamental to high-energy physics but remain challenging for classical simulations due to the sign problem and entanglement growth in real-time dynamics. Quantum computing offers a promising alternative for simulating such processes.
In this work, we study meson scattering in a (1+1)-dimensional $\mathbb{Z}_2$ lattice gauge theory coupled...
In this talk, we present an implementation of multiple fermion flavors in both the Kogut-Susskind and Wilson formulations for quantum simulations of (2+1)-dimensional Quantum Electrodynamics (QED). Our numerical results show a particular type of level crossing with one flavor of fermions at zero density for Wilson fermions, as expected from analytical Chern number calculations. Moving forward,...
