COMPASS: Multi-Domain Research

• COMPASS Program is a multi-domain initiative that integrates high-energy physics experiments, innovative AI strategies, and educational projects to advance structured measurement and analysis.
• It employs state-of-the-art methodologies such as DVCS, SIDIS, and Drell–Yan to map nucleon structure and validate QCD dynamics with high precision.
• The initiative also fosters diversity in STEM education and pioneers AI applications in multi-agent planning and medical segmentation, setting new standards in performance and benchmarking.

COMPASS Program refers to several major research initiatives across physics, artificial intelligence, and medical machine learning, each united by their emphasis on structured measurement, collaboration, and multi-dimensional analysis. The most established COMPASS programs are (i) the series of large-scale high-energy physics experiments at CERN (“COmmon Muon and Proton Apparatus for Structure and Spectroscopy”), (ii) a landmark grassroots physics education and diversity project at UC Berkeley known as the Compass Project, (iii) cooperative multi-agent reinforcement learning and planning systems in artificial intelligence, and (iv) a recent conformal prediction methodology for uncertainty quantification in deep learning. Below, each major program is detailed in its aims, methodologies, and empirical findings.

1. COMPASS at CERN: Multi-Dimensional Nucleon Structure and QCD Dynamics

The COMPASS facility at CERN is a fixed-target experiment designed to produce a three-dimensional, multi-observable mapping of the nucleon's quark and gluon substructure. Its scope encompasses four core experimental axes (Kabuss, 2011):

• Primakoff Reactions: Measurement of charged-pion and charged-kaon electric and magnetic polarizabilities, testing chiral perturbation theory predictions for $\alpha-\beta$ and $\alpha+\beta$. The differential cross-section is given by

$$\frac{d\sigma_{\pi A\to\pi\gamma A}}{dt} \approx \frac{Z^2\alpha_{\rm em}}{t^2} F_A^2(t) \left|\mathcal{A}_{\pi\gamma\to\pi\gamma}(s,t)\right|^2$$

where $\mathcal{A}(s,t)$ includes Born and polarizability terms.

• Generalised Parton Distributions (GPD) via Deeply Virtual Compton Scattering (DVCS): Mapping of GPDs $H(x,\xi,t)$ and $E(x,\xi,t)$ through beam-charge and spin asymmetries. The facility accesses the total quark angular momentum $J_q$ via Ji’s sum rule, utilizing kinematic reach $x_{\rm Bj}\in [0.01,0.1]$, $1 < Q^2 < 8\,\mathrm{GeV}^2$, and $|t|$ down to a few $10^{-3}$ GeV$^2$ (Ferrero, 2020, Sandacz, 2015).
• Transverse Momentum Dependent Distributions (TMDs) in Drell–Yan: COMPASS performs measurements of Sivers and Boer–Mulders functions in pion–proton Drell–Yan, testing the predicted sign-reversal of T-odd TMDs between SIDIS and Drell–Yan processes (Parsamyan, 2015, Chang, 2015).
• Semi-Inclusive Deep Inelastic Scattering (SIDIS): Detailed studies of multidimensional nucleon tomography and fragmentation functions using high-statistics muon beams on unpolarised and polarized targets (Sbrizzai, 2010, Parsamyan, 2015, Parsamyan, 2015).

Apparatus comprises a two-stage magnetic spectrometer with high-resolution tracking (Si dets., scintillating fibers, GEM, Micromegas), comprehensive particle identification, recoil proton detectors, and forward calorimetry. The setup enables kinematic, flavor, and spatial separation of key observables.

2. Structure and Methods: Physics Objectives and Analysis Formalism

COMPASS employs advanced theoretical, experimental, and analytical formalisms for disentangling signal modulations from background and for extracting QCD functions from measured asymmetries.

• GPD and DVCS Formalism: Cross-sections factorize into hard amplitude convoluted with GPDs. The leading-twist DVCS amplitude is

$$\mathcal{A}_{\rm DVCS} \propto \sum_q e_q^2 \int_{-1}^1 dx \left[ \frac{1}{x-\xi+i0} + \frac{1}{x+\xi-i0} \right] H^q(x,\xi,t)$$

Key observables include the $t$-dependence slope parameter $B(x_{\rm Bj})$ and beam-charge/spin asymmetries, used to extract nucleon tomography and constrain quark orbital angular momentum (Ferrero, 2020).

• TMD Factorization and SIDIS/DY: Structure functions encode convolutions over TMD PDFs and FFs:

$$\frac{d\sigma}{dx\,dz\,d\phi_h\,d^2\mathbf{p}_T} = \frac{\alpha_{\rm em}^2}{xyQ^2}\left[F_{UU,T} + \varepsilon_1 F_{UU}^{\cos\phi_h}\cos\phi_h + \varepsilon_2 F_{UU}^{\cos2\phi_h}\cos2\phi_h\right]$$

Sivers, Boer–Mulders, and Collins effects are isolated through azimuthal modulations and multidimensional (up to 4D) binning in $x$, $Q^2$, $z$, $p_T$ (Parsamyan, 2015, Parsamyan, 2015).

• Hadron Spectroscopy Methods: Partial Wave Analysis (PWA) in the isobar model is used to extract resonance parameters (mass, width) and quantum numbers from high-statistics exclusive final states (Austregesilo, 2012).

3. Empirical Results and Scientific Impact

Significant findings and performance metrics from the various COMPASS physics programs include:

Observable	Key Result(s)	Reference
Diversity in Physics Education (UC Berkeley)	45% female, 26% Latino, 58% STEM retention for Compass cohorts; cf. 21% women, 8.3% URM nationally	(Roth et al., 2012)
DVCS t-slope and Compton Form Factor	Projected $\Delta B \approx 0.2 \,\mathrm{GeV}^{-2}$ precision; unique $x$-dependent B(x) mapping	(Ferrero, 2020)
Sivers and Collins Amplitudes (SIDIS)	Sivers $A_{UT}^{\sin(\phi_h-\phi_S)}$ up to 0.08 for $h^+$; Collins “mirror” sign for $\pi^\pm$	(Parsamyan, 2015, Parsamyan, 2015, Martin, 2013)
Drell–Yan Sivers Test	First direct sign-reversal test between SIDIS and Drell–Yan; projected 1% asymmetry precision	(Parsamyan, 2015)
Hadron Resonance Identification	Confirmation of spin-exotic $\pi_1(1600)$, high-resolution baryon and meson spectroscopy	(Austregesilo, 2012)

Empirical confirmation of QCD-predicted phenomena—such as the sign-change of T-odd TMDs and the multidimensional structure of parton distributions—demonstrates the explanatory power of the combined experimental-theoretical platform.

4. Education, Diversity, and Professional Development: The Compass Project at UC Berkeley

The Compass Project at UC Berkeley established a new paradigm in retention and inclusion in undergraduate physics education (Roth et al., 2012). Key structural features:

• Summer bridge program for incoming freshmen, with a curriculum built around open-ended, modeling-based physics investigations.
• Semester-long courses: physical modeling in fall (since 2009), measurement and error analysis in spring (since 2012), and a pilot transfer seminar (2011).
• Peer and near-peer mentoring, academic support, and cultural/social infrastructure, including paper groups and monthly social events.
• Outcomes show Compass cohorts are approximately twice as diverse as national physics averages in gender and underrepresented minority (URM) participation, with a 58% six-year STEM completion rate vs. 38% nationally.

Pedagogical innovation includes student-driven inquiry, team-based modeling, error analysis, and iterative feedback. Graduate participation in leadership, curriculum design, and mentoring is central, with documented faculty and student satisfaction.

5. COMPASS in AI and Medical Machine Learning

Multiple recent initiatives adopt the COMPASS acronym in AI and machine learning, emphasizing principled coordination, planning, or uncertainty quantification (Wan et al., 9 Oct 2025, Cheung et al., 26 Sep 2025, Meaden et al., 19 Aug 2025, Zhang et al., 22 Jul 2025, Li et al., 14 Feb 2025):

• Long-Horizon Reasoning in LLM Agents: COMPASS (Context-Organized Multi-Agent Planning and Strategy System) structures LLM agents via (1) a main tactical agent, (2) a meta-thinker for strategic oversight, (3) a context manager for brief synthesis. Dual-loop orchestration with explicit policies for strategic triggers, context pruning, and parallel test-time scaling increases Pass@1 up to 20% over multi-agent baselines across standard benchmarks (Wan et al., 9 Oct 2025).
• Conformal Prediction for Medical Segmentation: COMPASS (Conformal Metric Perturbation Along Sensitive Subspaces) generates efficient prediction intervals for segmentation-derived metrics by calibrating along principal directions in the latent feature space most correlated with target metrics (e.g., lesion area), yielding up to 50% narrower intervals than output-space methods under valid coverage (Cheung et al., 26 Sep 2025).
• Code Generation Benchmarking: COMPASS (COdility’s Multi-dimensional Programming ASSessment) establishes a tri-axis evaluation for code generation—correctness, efficiency, and code quality—using a curated Codility dataset with human baselines. Analyses show that functional correctness is insufficient for production utility, requiring explicit assessment of runtime scaling and maintainability (Meaden et al., 19 Aug 2025).
• Multi-Agent Monitoring and Planning: COMPASS frameworks in MARL settings blend spatio-temporal attention, agent-specific GP belief modeling, and entity-based multi-hop communication to enhance coordination and adaptivity in persistent monitoring and StarCraft-style planning domains (Zhang et al., 22 Jul 2025, Li et al., 14 Feb 2025).

6. Methodological and Societal Lessons: Replicability, Sustainability, and Transfer

Analysis of the educational COMPASS Project at UC Berkeley identified successful replication components applicable to other domains:

• Early intervention—especially the pre-college summer window—is critical for building community and identity.
• Near-peer mentoring and collaborative, inquiry-driven structure counteract isolation and disengagement.
• Sustained funding, shared governance, and responsive program iteration are necessary for longevity and impact.
• Adaptation to “local context” is required; rigid templating across institutions fails.

AI-oriented COMPASS systems leverage domain-specific inductive biases (e.g., latent representations, structural mapping of tasks, multi-level context aggregation) and rigorous uncertainty quantification. This reflects an overarching methodological principle: coupling principled theoretical modeling with deep access to system structure yields robust gains in performance, efficiency, and reliability.

7. Outlook and Continuing Developments

The COMPASS suite of programs continues to set standards in their fields:

• In high-energy physics, the COMPASS II upgrade and subsequent measurements are closing precision gaps in nucleon imaging, validating transversity frameworks, and informing phenomenological global fits for GPD and TMD extractions (Kabuss, 2011, Ferrero, 2020).
• In AI, multi-agent COMPASS approaches have achieved superior sample efficiency and interpretability in cooperative domains, showing translation potential for robotics and networked resource allocation (Li et al., 14 Feb 2025, Zhang et al., 22 Jul 2025).
• The robust multi-metric and multidimensional benchmarking standards of COMPASS have become a reference for fair, real-world model assessment in code generation and beyond (Meaden et al., 19 Aug 2025).
• Medical imaging methods leveraging conformal prediction under the COMPASS framework have enabled practical, coverage-valid uncertainty quantification for clinically relevant segmentation metrics (Cheung et al., 26 Sep 2025).

The programmatic thread uniting these endeavors is a commitment to multidimensional, structured measurement, interpretability, and educational or methodological innovation, often realized through community-led and highly collaborative architectures.