arXiv subjects

Lorenzo Uboldi

Publications and source records attributed to Lorenzo Uboldi.

5 recordsLinked to original sources

arXiv2026

Physics at the Edge: Benchmarking Quantisation Techniques and the Edge TPU for Neutrino Interaction Recognition

This work presents a comprehensive benchmark of different quantisation techniques for convolutional neural networks applied to neutrino interaction recognition. Utilising simulation for a generic liquid argon time-projection chamber, models are quantised and then deployed on the Google Coral Edge TPU. Models are tasked with recognising which neutrino interaction is simulated in the image between neutral current, muon-neutrino charged current, and electron-neutrino charged current. Four Keras models are tested, and accuracy is measured across two different pipelines: using post-training integer quantisation and quantisation-aware training. Inference speed is benchmarked against an AMD EPYC 7763 CPU and NVIDIA A100 GPU. A study of the energy consumption is also presented, with attention to potential costs and environmental issues. Results show that, among the four models tested, accuracy degradation is limited and, in particular, Inception V3 presents almost no accuracy degradation across the two quantisation and deployment pipelines. The speed of the edge TPU is comparable to that of the CPU, and one order of magnitude slower than the GPU. Moreover, the energy consumption of all models deployed on the edge TPU is several orders of magnitude lower than that of the CPU and GPU. In the energy consumption-latency parameter space, CPU, GPU, and edge TPU performances can be clearly separated. This paper explores possible future integrations of edge AI technologies with neutrino physics.

physics.ins-det↗

arXiv2025

Entangled-photon time- and frequency-resolved optical spectroscopy

Classical time-resolved optical spectroscopy experiments are performed using sequences of ultrashort light pulses, with photon fluxes incident on the sample which are many orders of magnitude higher than real-world conditions corresponding to sunlight illumination. Here we overcome this paradigm by exploiting quantum correlations to perform time-resolved spectroscopy with entangled photons. Starting from spontaneous parametric down-conversion driven by a continuous-wave laser, we exploit the temporal entanglement between randomly generated signal/idler pairs to obtain temporal resolution, and their spectral entanglement to select the excitation frequency. We also add spectral resolution in detection, using a Fourier transform approach which employs a common-path interferometer. We demonstrate the potential of our entangled-photon streak camera by resolving, at the single-photon level, excitation energy transfer cascades from LH2 to LH1 in the photosynthetic membrane and disentangling the lifetimes of two dyes in a mixture. We show that time-resolved spectroscopy with quantum light can be performed without compromising measurement time, recording a fluorescence time trace in less than a minute even for samples with low quantum yield, which can be reduced to sub-second times with acceptable signal-to-noise ratio. Our results provide a new approach to ultrafast optical spectroscopy, where experiments are performed under conditions comparable to real-world sunlight illumination.

quant-ph↗

arXiv2023

Optical microcavities as platforms for entangled photon spectroscopy

Optical microcavities are often proposed as platforms for spectroscopy in the single- and few-photon regime due to strong light-matter coupling. For classical-light spectroscopies, an empty microcavity simply acts as an optical filter. However, we find that in the single- or few-photon regime treating the empty microcavity as an optical filter does not capture the full effect on the quantum state of the transmitted photons. Focusing on the case of entangled photon-pair spectroscopy, we consider how the propagation of one photon through an optical microcavity changes the joint spectrum of a frequency-entangled photon pair. Using the input-output treatment of a Dicke model, we find that propagation through a strongly coupled microcavity above a certain coupling threshold enhances the entanglement entropy between the signal and idler photons. These results show that optical microcavities are not neutral platforms for quantum-light spectroscopies and their effects must be carefully considered when using change in entanglement entropy as an observable.

quant-ph↗

arXiv2023

Measurement principles for quantum spectroscopy of molecular materials with entangled photons

Nonlinear spectroscopy with quantum entangled photons is an emerging field of research that holds the promise to achieve a superior signal-to-noise ratio and effectively isolate many-body interactions. Photon sources used for this purpose however lack the frequency tunability and spectral bandwidth demanded by contemporary molecular materials. Here, we present design strategies for efficient spontaneous parametric downconversion to generate biphoton states with adequate spectral bandwidth and at visible wavelengths. Importantly, we demonstrate, by suitable design of the nonlinear optical interaction, the scope to engineer the degree of spectral correlations between the photons of the pair. We also present an experimental methodology to effectively characterize such spectral correlations. Importantly, we believe that such a characterization tool can be effectively adapted as a spectroscopy platform to optically probe system-bath interactions in materials.

physics.optics↗

arXiv2021

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques -- A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

physics.ins-det↗