Orchard Sciences

Orchard Sciences

Independentscientific research.

Quantum measurement, predictive analytics,
and the evaluation of AI systems.

Explore the research programs

Research programs

Reliable information.
Consequential decisions.

Orchard Sciences researches the reliability of measurement and decision systems. The work connects physical sensing, forecasting, and AI-assisted analysis through a common problem: extracting useful information when evidence is noisy, incomplete, or changing.

LATTICE, COPPERLINE, and IRONWOOD address different parts of that problem. Their technical briefs set out the models, operating constraints, and evaluation methods that define each program.

OS—01Quantum measurement

LATTICE

Weak-signal estimation under finite acquisition time.

A sensor can be intrinsically sensitive and still produce an unreliable estimate. Longer interrogation may accumulate more signal while also losing coherence; additional samples cost time, power, and readout overhead. LATTICE examines those tradeoffs at the level of the estimator and the full acquisition cycle.

Research focus
Contrast loss, calibration drift, finite samples, and the cost of repeated measurement.
Application context
Relevant to field sensing, timing, and interferometric measurement, where a small change in the quantity of interest must be distinguished from drift and noise.
Evaluation basis
Error at a matched acquisition budget; uncertainty coverage; robustness to a misspecified noise model.
Read the LATTICE technical brief

OS—02Predictive analytics

COPPERLINE

Forecasting when observations and operating conditions change.

An operational forecast is made before all the relevant observations are known. Reports arrive late, measurements are revised, and demand or operating conditions can change between training and use. COPPERLINE evaluates forecasts against the information that was actually available at each decision point.

Research focus
Delayed observations, changing regimes, horizon-specific uncertainty, and asymmetric decision costs.
Application context
Relevant to resource planning, replenishment, maintenance, and capacity allocation—decisions whose costs depend on lead time and on which direction a forecast is wrong.
Evaluation basis
Performance against simple baselines; interval coverage and width; decision cost under changed conditions.
Read the COPPERLINE technical brief

OS—03AI evaluation

IRONWOOD

Evidence-grounded analysis with explicit decision boundaries.

A fluent response can cite a real document and still misrepresent it. Sources may disagree, refer to different dates, or describe different entities with similar names. IRONWOOD examines the chain from source selection to individual claims, with abstention and review as measurable system behaviors.

Research focus
Claim-level support, source versions, contradictions, missing evidence, and permission boundaries.
Application context
Relevant to technical document review, incident assessment, and analysis across changing records, where an unsupported conclusion can be more costly than an explicit gap.
Evaluation basis
Support and citation accuracy; retrieval coverage; appropriate abstention; review effort and action-boundary failures.
Read the IRONWOOD technical brief

Research practice

A result needs a record.

A useful result includes the conditions under which it was obtained and the information needed to challenge it. These principles structure evaluation across all three programs.

01

Define the comparison.

State the hypothesis, baseline, resource budget, and failure criteria before interpreting performance.

02

Preserve reproducibility.

Version data, code, configurations, and evaluation procedures. Keep provenance attached to each result.

03

Report the boundary.

Document uncertainty, negative results, and the conditions under which a conclusion no longer holds.

Orchard Sciences

Research correspondence.

For discussion of a research question, evaluation method, or potential collaboration.

hello@orchardsciences.com

Correspondence