Project HGE (Hypothesis Generation Engine)
Project HGE operationalizes the scientific method as infrastructure. It formulates testable hypotheses, designs experiments to maximize information gain, executes them on real instruments under operational constraints, and updates confidence based on observed evidence. The system is instrument-agnostic, provenance-aware, and designed to function in environments characterized by noise, drift, and uncertainty. HGE represents a methodological approach to automated scientific discovery grounded in rigorous validation and reproducibility.
Intended for institutional and research audiences. Public materials are released selectively.
How it works
HGE implements a four-stage methodology that mirrors the scientific method while operating autonomously under real-world constraints.
Hypothesis generation
System formulates testable hypotheses based on current knowledge state, uncertainty estimates, and domain constraints. Hypotheses are structured to enable falsification and quantitative evaluation.
Experiment design
Experiments are designed to maximize expected information gain while respecting instrument capabilities, resource constraints, and operational limits. Design prioritizes hypotheses with highest epistemic value.
Execution on real instruments
Experiments are executed on physical instruments in operational environments. Execution accounts for noise, drift, calibration uncertainty, and environmental factors. Full provenance is maintained.
Belief update and iteration
Observed results are used to update confidence in hypotheses through Bayesian reasoning. Updated beliefs inform the next cycle of hypothesis generation, creating a continuous discovery loop.
Methodological principle: Each cycle increases confidence in validated hypotheses while identifying new areas of uncertainty, enabling systematic exploration of complex problem spaces.
Current validation
HGE is currently being validated in a demanding physical environment to stress-test its methodology under real-world operational constraints.
Live remote quantum hardware as physical stress-test environment
The methodology is being validated using live remote quantum computing hardware. Quantum systems present significant operational challenges: high noise levels, temporal drift, calibration uncertainty, and limited coherence times. These characteristics make quantum hardware a rigorous test environment for validating HGE's ability to function under adverse physical conditions.
Note: Quantum hardware is used as a validation environment for the methodology, not as the primary application domain. The goal is to stress-test HGE's approach in a physically demanding context.
Why it matters
HGE addresses the challenge of systematic discovery in domains where experimentation is expensive, time-consuming, or constrained by physical limitations.
Current application domains
HGE is currently focused on astronomy and physics research, where observational constraints, instrument availability, and data acquisition costs make systematic hypothesis testing particularly valuable. The methodology enables efficient exploration of parameter spaces and identification of promising research directions under resource constraints.
Future application directions
Future directionFuture applications may extend to biology and health research, where similar challenges exist: high experimental costs, long feedback cycles, and complex parameter spaces. Potential applications include drug discovery optimization, biological pathway exploration, and clinical trial design. These applications represent future research directions and are not currently active.
Core value proposition: HGE enables systematic, resource-efficient exploration of complex problem spaces where traditional approaches are limited by cost, time, or physical constraints.
Research access & technical briefings
HGE technical materials are maintained internally and shared selectively with qualified research partners and institutional collaborators.
Controlled research access
Project HGE technical papers, system documentation, and validation materials are maintained internally and shared selectively with research partners, funding agencies, and institutional collaborators.
Public releases will follow peer review, partner validation, and governance review.
Research briefings are provided to qualified partners following institutional review. Materials are shared under appropriate confidentiality and collaboration frameworks.
Discuss research collaboration
Institutions and research organizations interested in exploring HGE methodology, validation approaches, or potential collaborative applications are invited to initiate structured dialogue through the institutional engagement process.
Initiate research dialogueEngagement follows structured institutional dialogue protocols. Response times vary based on inquiry complexity and alignment with current research priorities.