arXiv subjects

Mia Tosi

Publications and source records attributed to Mia Tosi.

6 recordsLinked to original sources

arXiv2026

On the Codesign of Scientific Experiments and Industrial Systems

The optimization of large experiments in fundamental science, such as detectors for subnuclear physics at particle colliders, shares with the optimization of complex systems for industrial or societal applications the common issue of addressing the inter-relation between parameters describing the hardware used in data production and parameters used to analyse those data. While in many cases this coupling can be ignored -- when the problem can be successfully factored into simpler sub-tasks and the latter addressed serially -- there are situations in which that approach fails to converge to the absolute maximum of expected performance, as it results in a mis-alignment of the optimized hardware and software solutions. In this work we consider a few use cases of interest in fundamental science collected primarily from particle physics and related areas, and a pot-pourri of industrial and societal applications where the matter is similarly of relevance. We discuss the emergence of strong hardware-software coupling in some of those systems, as well as co-design procedures that may be deployed to identify the global maximum of their relevant utility functions. We observe how numerous opportunities exist to advance methods and tools for hardware-software co-design optimization, bridging fundamental science and industry through application- and challenge-driven projects, and shaping the future of scientific experiments and industrial systems.

physics.ins-det↗

arXiv2025

Unsupervised Particle Tracking with Neuromorphic Computing

We study the application of a neural network architecture for identifying charged particle trajectories via unsupervised learning of delays and synaptic weights using a spike-time-dependent plasticity rule. In the considered model, the neurons receive time-encoded information on the position of particle hits in a tracking detector for a particle collider, modeled according to the geometry of the Compact Muon Solenoid Phase II detector. We show how a spiking neural network is capable of successfully identifying in a completely unsupervised way the signal left by charged particles in the presence of conspicuous noise from accidental or combinatorial hits. These results open the way to applications of neuromorphic computing to particle tracking, motivating further studies into its potential for real-time, low-power particle tracking in future high-energy physics experiments.

hep-ex↗

arXiv2022

Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper

The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, given the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, "experience-driven" layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized by means of a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters. In this document we lay down our plans for the design of a modular and versatile modeling tool for the end-to-end optimization of complex instruments for particle physics experiments as well as industrial and medical applications that share the detection of radiation as their basic ingredient. We consider a selected set of use cases to highlight the specific needs of different applications.

physics.ins-det↗

arXiv2016

Analytical parametrization and shape classification of anomalous HH production in the EFT approach

In this document we study the effect of anomalous Higgs boson couplings on non-resonant pair production of Higgs bosons ($HH$) at the LHC. We explore the space of the five parameters $κ_λ$, $κ_{t}$, $c_2$, $c_g$, and $c_{2g}$ in terms of the corresponding kinematics of the final state, and describe a partition of the space into a limited number of regions featuring similar phenomenology in the kinematics of $HH$ final state. We call clusters the sets of points belonging to the same region; to each cluster corresponds a representative point which we call a benchmark. We discuss a possible technique to estimate the sensitivity of an experimental search to the kinematical differences between the phenomenology of the benchmark points and the rest of the parameter space contained in the corresponding cluster. We also provide an analytical parametrization of the cross-section modifications that the variation of anomalous couplings produces with respect to standard model $HH$ production along with a recipe to translate the results into other parameter-space bases. Finally, we provide a preliminary analysis of variations in the topology of the final state within each region based on recent LHC results.

hep-ph↗

arXiv2016

Higgs Pair Production: Choosing Benchmarks With Cluster Analysis

New physics theories often depend on a large number of free parameters. The precise values of those parameters in some cases drastically affect the resulting phenomenology of fundamental physics processes, while in others finite variations can leave it basically invariant at the level of detail experimentally accessible. When designing a strategy for the analysis of experimental data in the search for a signal predicted by a new physics model, it appears advantageous to categorize the parameter space describing the model according to the corresponding kinematical features of the final state. A multi-dimensional test statistic can be used to gauge the degree of similarity in the kinematics of different models; a clustering algorithm using that metric may then allow the division of the space into homogeneous regions, each of which can be successfully represented by a benchmark point. Searches targeting those benchmark points are then guaranteed to be sensitive to a large area of the parameter space. In this document we show a practical implementation of the above strategy for the study of non-resonant production of Higgs boson pairs in the context of extensions of the standard model with anomalous couplings of the Higgs bosons. A non-standard value of those couplings may significantly enhance the Higgs pair production cross section, such that the process could be detectable with the data that the Large Hadron Collider will collect in Run 2.

hep-ph↗

arXiv2008

Energy Calibration of b-Quark Jets with Z->b-bbar Decays at the Tevatron Collider

The energy measurement of jets produced by b-quarks at hadron colliders suffers from biases due to the peculiarities of the hadronization and decay of the originating B hadron. The impact of these effects can be estimated by reconstructing the mass of Z boson decays into pairs of b-quark jets. From a sample of 584 pb-1 of data collected by the CDF experiment in 1.96 TeV proton-antiproton collisions at the Tevatron collider, we show how the Z signal can be identified and measured. Using the reconstructed mass of Z candidates we determine a jet energy scale factor for b-quark jets with a precision better than 2%. This measurement allows a reduction of one of the dominant source of uncertainty in analyses based on high transverse momentum b-quark jets. We also determine, as a cross-check of our analysis, the Z boson cross section in hadronic collisions using the b-bbar final state as sigma x B(Z->b-bbar) = 1578 +636 -410 pb.

hep-ex↗