Deterministic Trust Pipelines: A Reference Architecture for Auditable QIST Systems

Abstract

As Quantum Information Science and Technology (QIST) systems transition from research environments into operational, institutional, and safety-critical contexts, trust becomes a systems property rather than a feature. Trust in this setting requires that decisions, plans, and actions produced by complex computational pipelines are deterministic, auditable, and attributable.

This Reference Architecture defines a deterministic trust pipeline for QIST systems. The architecture separates probabilistic computation from deterministic commitment, establishes cryptographic provenance for system artifacts, and enables long-lived auditability independent of specific algorithms or implementations. The intent is to provide a reusable architectural pattern applicable across quantum-adjacent, cryptographic, and autonomous systems without prescribing concrete protocols or vendors.

This document is informational and pre-standard in nature. It does not define mandatory requirements, certify implementations, or assert regulatory authority.

Review, version advancement, and retraction are governed by QIST-RA-2025-001.

1. Introduction

Many QIST systems integrate probabilistic computation, heuristic optimization, or adaptive learning components. While such techniques may be appropriate during exploration or planning, they pose challenges when system outputs must be trusted by external parties.

Institutions deploying QIST systems must be able to demonstrate:

• What decision was made
• Under what constraints
• Using which inputs and assumptions
• With what verification

This Reference Architecture addresses these needs by defining a deterministic trust pipeline that governs how system outputs are committed, recorded, and audited.

2. Architectural Objectives

The deterministic trust pipeline is designed to satisfy the following objectives:

• Determinism at Commitment: Final decisions and actions are deterministic, even if upstream processes are probabilistic.
• Auditability: Independent parties can reconstruct decision context and verify outcomes.
• Separation of Concerns: Planning, verification, and execution are distinct stages with explicit boundaries.
• Cryptographic Provenance: Artifacts are bound to their origin and context using cryptographic mechanisms.
• Longevity: Records remain interpretable and verifiable over long time horizons.

3. High-Level Pipeline Overview

The deterministic trust pipeline consists of five primary stages:

1. Ingestion
2. Planning / Optimization
3. Verification
4. Commitment
5. Recording and Audit

Each stage produces artifacts that are either transient (non-authoritative) or persistent (authoritative).

4. Pipeline Stages

4.1 Ingestion

The ingestion stage collects inputs required for planning and decision-making, including:

• Environmental data
• Policy constraints
• System state
• External signals

All inputs are normalized and versioned. Inputs MAY be incomplete or uncertain at this stage.

4.2 Planning and Optimization

Planning processes MAY include:

• Probabilistic algorithms
• Heuristic solvers
• Quantum or hybrid optimizers
• Machine learning models

Outputs of this stage are proposals, not commitments. Multiple candidate plans MAY be produced.

Crucially, planning outputs are not directly executed.

4.3 Verification

The verification stage evaluates candidate plans against deterministic criteria, such as:

• Policy compliance
• Safety constraints
• Cryptographic correctness
• Resource bounds

Verification is deterministic and repeatable. Plans that fail verification are discarded.

4.4 Commitment

The commitment stage selects a single verified plan and produces an authoritative decision artifact.

Characteristics of commitment artifacts include:

• Deterministic content
• Cryptographic signatures
• Explicit references to inputs, constraints, and verification results

Once committed, a decision is immutable.

4.5 Recording and Audit

Committed artifacts are recorded in an append-only audit substrate, such as:

• Hash-chained logs
• Merkle-tree structures
• Signed checkpoints

The audit substrate enables:

• Historical reconstruction
• Independent verification
• Detection of tampering or omission

5. Artifact Taxonomy

The architecture distinguishes between:

• Transient Artifacts: Planning outputs, intermediate states, exploratory data
• Persistent Artifacts: Committed decisions, verification results, policy snapshots

Only persistent artifacts are considered authoritative.

6. Trust Boundaries and Interfaces

Explicit trust boundaries separate pipeline stages.

Each boundary defines:

• Accepted inputs
• Validation requirements
• Output guarantees

This prevents implicit trust propagation from probabilistic components into deterministic commitments.

7. Failure Modes and Recovery

The architecture anticipates failure conditions, including:

• Incomplete or inconsistent inputs
• Verification failures
• Audit substrate unavailability

In all cases, the system MUST fail safely by refusing commitment rather than executing unverifiable actions.

Recovery procedures MAY include re-ingestion, re-planning, or deferred commitment.

8. Applicability Across Domains

While motivated by QIST systems, the deterministic trust pipeline applies to:

• Post-quantum cryptographic systems
• Autonomous platforms
• Distributed trust architectures
• Safety-critical decision systems

The architecture is intentionally abstract to support reuse across domains.

9. Limitations and Non-Goals

This Reference Architecture:

• Does not mandate specific algorithms or technologies
• Does not eliminate uncertainty in upstream computation
• Does not replace organizational governance or oversight

It provides structural discipline, not absolute guarantees.

10. Conclusion

Deterministic trust pipelines provide a structural foundation for deploying advanced computational systems in environments where accountability, auditability, and long-term trust are mandatory.

By separating probabilistic exploration from deterministic commitment and embedding cryptographic provenance throughout the pipeline, institutions can reduce systemic risk while retaining the benefits of advanced computation.

The QIST Foundation publishes this Reference Architecture to support responsible system design, evaluation, and governance in QIST and related domains.

---

End of QIST-RA-2025-001 (v0.1)