INITIALIZING

CHRONA

Temporal Compute Layer

Explore

Time is programmable

CHRONA decouples time from block height. Record state. Rewind execution. Replay history. Build applications that exist outside linear time constraints.

Temporal State

Capture and reconstruct any point in application history with sub-second precision.

Parallel Histories

Execute multiple timeline branches simultaneously. Merge outcomes across realities.

Causal Tracing

Map every state transition. Understand causality across distributed systems.

State Convergence

Merge divergent timelines with automatic conflict resolution and consistency guarantees.

Built for scale

A modular stack designed to handle temporal complexity at any scale. From single-application state management to cross-chain orchestration.

  • Core — Consensus and temporal indexing
  • Mesh — Distributed synchronization layer
  • Vault — Immutable historical storage
  • SDK — Developer interface and tooling
Documentation
CHRONA Architecture

Quickstart

Initialize your first temporal instance in under 60 seconds.

$
example.js
JavaScript
// Import the temporal SDK import { ChronaClient, Timeline } from '@chrona/sdk'; // Initialize client with mesh connection const chrona = new ChronaClient({ endpoint: 'https://mesh.chrona.network', apiKey: process.env.CHRONA_KEY }); // Create a new timeline branch const timeline = await chrona.createTimeline({ origin: 'genesis', mode: 'parallel' }); // Execute state transition with temporal lock const result = await timeline.execute(async (state) => { state.set('balance', 1000); return state.commit(); }); // Rewind to specific timestamp const snapshot = await timeline.rewind({ timestamp: 1704067200000, preserve: true }); console.log('Temporal state captured at:', snapshot.checkpoint);

Your application now operates outside linear time constraints. State transitions are recorded, replayable, and can branch into parallel execution paths.

Core Concepts

Understanding temporal mechanics and causality flow.

Timeline Execution Model
Genesis
Origin state
Branch Point
Timeline split
Parallel Exec
Multiple paths
Convergence
State merge
branching.js
JavaScript
// Create multiple parallel timelines const branches = await Promise.all([ timeline.branch({ id: 'scenario-a' }), timeline.branch({ id: 'scenario-b' }), timeline.branch({ id: 'scenario-c' }) ]); // Execute different state transitions in each branch await branches[0].execute(() => applyStrategy('aggressive')); await branches[1].execute(() => applyStrategy('conservative')); await branches[2].execute(() => applyStrategy('balanced')); // Compare outcomes across realities const outcomes = await chrona.compare(branches); // Merge optimal path back to main timeline const optimal = outcomes.maxBy('efficiency'); await timeline.merge(optimal, { strategy: 'fast-forward' });
T₀ — Genesis Block
Initial state checkpoint. All timelines branch from this origin point.
T₁ — First Branch
Timeline splits into parallel execution paths with isolated state.
T₂ — State Divergence
Branches execute independently. State differences accumulate.
T₃ — Convergence
Optimal timeline selected and merged back to main execution path.

Interactive Demo

Experience temporal control in real-time.

✓ Demo initialized Timeline ID: tmp-demo-8f4a9c2e Current State: { counter: 0, branches: [] } Ready for temporal operations...
0
Operations
1
Active Branches
0
Checkpoints
~2ms
Avg Latency

Temporal Control API

Methods for manipulating time-based execution flow.

Method
timeline.rewind()
Revert application state to a specific point in historical execution without losing forward state data.
Parameters
timestamp
number
Unix millisecond timestamp of target state
preserve
boolean
Whether to maintain forward state in parallel branch
mode
'hard' | 'soft' | 'shadow'
Rewind execution strategy
Method
timeline.branch()
Create a parallel timeline fork from the current state checkpoint. Branches execute independently until merged.
Parameters
id
string
Unique identifier for the branch timeline
isolation
'full' | 'partial' | 'shared'
State isolation level between branches
Method
timeline.replay()
Re-execute historical state transitions with modified parameters or environment conditions.
Parameters
range
[number, number]
Timestamp range to replay [start, end]
override
object
State modifications to apply during replay

State Management

Immutable state capture and reconstruction across temporal boundaries.

state-capture.js
JavaScript
// Capture full application state snapshot const snapshot = await chrona.captureState({ depth: 'recursive', include: ['memory', 'storage', 'network'], compression: true }); // Store in distributed vault const checkpoint = await chrona.vault.store(snapshot, { replication: 3, encryption: 'aes-256' }); // Later: reconstruct exact state const restored = await chrona.reconstructState(checkpoint.id); await timeline.applyState(restored);
State Capture Architecture
Application
Live state
Serializer
State encoding
Vault
Immutable storage
Recovery
State reconstruction

Mesh Synchronization

Cross-instance coordination and temporal consensus protocols.

mesh-sync.js
JavaScript
// Connect to mesh network const mesh = await chrona.connectMesh({ protocol: 'tcp+tls', nodes: ['mesh-1.chrona.network', 'mesh-2.chrona.network'], consensus: 'temporal-bft' }); // Subscribe to global timeline events mesh.on('checkpoint', async (event) => { console.log('Global checkpoint:', event.height); await timeline.sync(event.state); }); // Broadcast state transition to network await mesh.broadcast({ type: 'state-transition', timeline: timeline.id, delta: stateDiff, signature: await chrona.sign(stateDiff) });

Protocol Layers

Deep dive into the four-layer architecture powering temporal computation.

CHRONA Stack Architecture
SDK Layer
Developer interface, client libraries, tooling
Vault Layer
Immutable storage, state archival, retrieval
Mesh Layer
P2P synchronization, consensus coordination
Core Layer
Temporal indexing, causality engine, execution

Each layer operates independently yet maintains strict temporal consistency through cryptographic proofs and distributed consensus mechanisms.

Temporal Consensus

Byzantine fault-tolerant consensus adapted for non-linear temporal execution.

consensus-flow
Pseudocode
// Temporal BFT Consensus Round function temporalConsensus(proposals) { // Phase 1: Temporal ordering const ordered = orderByTimestamp(proposals); // Phase 2: Causality validation const valid = ordered.filter(p => validateCausalChain(p) && verifySignatures(p) ); // Phase 3: Network voting (>2/3 threshold) const votes = await mesh.collectVotes(valid); const approved = votes.filter(v => v.weight >= 0.67); // Phase 4: Commit to global timeline await commitCheckpoint(approved, { height: currentHeight + 1, timestamp: consensusTime(), stateRoot: merkleRoot(approved) }); return approved; }

The consensus mechanism ensures that all nodes agree on temporal ordering even when state transitions occur across different timeline branches.

Performance Metrics

Real-world performance characteristics across network conditions.

2.3ms
Avg Rewind Latency
15k
Ops/Second
99.97%
Consensus Success
4.2s
State Finality
Operation p50 Latency p95 Latency p99 Latency Throughput
Timeline Branch 1.2ms 3.4ms 8.1ms 18.5k/s
State Capture 2.8ms 6.2ms 14.3ms 12.3k/s
Temporal Rewind 2.3ms 5.1ms 11.7ms 15.1k/s
Mesh Sync 3.9ms 8.6ms 18.2ms 9.7k/s
State Merge 4.5ms 10.3ms 22.8ms 7.2k/s

CHRONA: A Temporal Compute Layer

Decoupling Time from Block Height in Distributed Systems

Abstract

We present CHRONA, a novel temporal compute layer that decouples time from block height, enabling applications to record, rewind, and replay state across arbitrary temporal boundaries. Traditional blockchain systems bind state transitions to linear block sequences, creating fundamental limitations in temporal flexibility and parallel execution capabilities.

CHRONA introduces a four-layer architecture—Core, Mesh, Vault, and SDK—that enables temporal state management without sacrificing consensus guarantees. Through temporal indexing, parallel timeline execution, and causal tracing, applications can explore multiple execution paths simultaneously and merge optimal outcomes.

Our temporal Byzantine Fault Tolerance (tBFT) consensus mechanism ensures network agreement on state ordering even when transitions occur across non-linear timeline branches. We demonstrate sub-3ms rewind latency and 15k operations per second in distributed environments, achieving 99.97% consensus success rates across varied network conditions.

2.3ms
Rewind Latency
15k
Ops/Second
99.97%
Consensus Rate
4 Layers
Architecture

1. Introduction

The linear nature of blockchain consensus creates inherent limitations in how applications can interact with historical state. Once a transaction is finalized, reverting or replaying state requires complex rollback mechanisms that often compromise consistency guarantees.

CHRONA addresses this limitation by introducing temporal programmability as a first-class primitive. Rather than treating time as an immutable arrow pointing forward, we enable applications to navigate temporal dimensions with the same flexibility as spatial data structures.

1.1 Problem Statement

Traditional distributed systems face three core temporal limitations:

(1) Linear State Progression: State transitions follow strict sequential ordering, preventing parallel execution of alternative scenarios.

(2) Irreversible Finality: Once consensus is reached, historical states become inaccessible without full replay of all intermediate transitions.

(3) Causality Opacity: Understanding how specific states emerged requires manual correlation of distributed log data across multiple systems.

1.2 Our Approach

CHRONA introduces temporal indexing that maintains causal relationships across non-linear execution paths. Applications can branch timelines, execute state transitions independently, and merge outcomes based on computed optimality criteria.

2. System Architecture

CHRONA's architecture consists of four primary layers, each responsible for specific aspects of temporal computation and consensus coordination.

2.1 Core Layer

The Core layer implements temporal indexing and causality tracking. Every state transition receives a temporal coordinate T(h, b, s) where h represents height, b represents branch identifier, and s represents sequence position within the branch.

T(h, b, s) → State(h, b, s)
Causal(T₁, T₂) ⟺ (h₁ < h₂) ∨ (h₁ = h₂ ∧ s₁ < s₂)

2.2 Mesh Layer

The Mesh layer provides peer-to-peer synchronization across distributed nodes. It implements our temporal BFT consensus protocol, ensuring network agreement on temporal ordering even when state transitions occur across independent timeline branches.

2.3 Vault Layer

The Vault layer maintains immutable state archives with content-addressed storage. Every checkpoint generates a cryptographic commitment that can be retrieved and reconstructed with perfect fidelity.

2.4 SDK Layer

The SDK layer exposes developer-friendly interfaces for temporal operations. Applications interact with timelines, branches, and state through high-level abstractions that hide distributed systems complexity.

3. Temporal Consensus Protocol

Traditional BFT consensus assumes linear state progression. CHRONA extends BFT to handle parallel timeline execution through temporal ordering constraints and branch convergence rules.

3.1 Temporal Ordering

All state transitions receive timestamps from a distributed clock synchronization protocol. Nodes order proposals by timestamp, with causality validation ensuring logical consistency across branches.

Order(T₁, T₂) = {
  T₁.timestamp < T₂.timestamp : T₁ ≺ T₂
  T₁.timestamp = T₂.timestamp : hash(T₁) < hash(T₂)
}

3.2 Consensus Rounds

Each consensus round proceeds in four phases: temporal ordering, causality validation, network voting, and checkpoint commitment. The network requires >2/3 agreement to finalize any temporal state transition.

3.3 Branch Convergence

When parallel branches merge, CHRONA applies conflict resolution based on application-defined merge strategies. The protocol guarantees that all nodes converge to identical final states regardless of merge order.

4. Implementation Details

Our reference implementation demonstrates production-grade performance characteristics across varied network topologies and failure scenarios.

4.1 State Serialization

Application state undergoes recursive serialization with compression and encryption before vault storage. We employ content-addressed storage with Merkle proofs for integrity verification.

4.2 Network Protocol

The Mesh layer implements a gossip-based synchronization protocol over TCP+TLS. Nodes maintain partial views of the network and probabilistically forward temporal proposals to achieve rapid convergence.

4.3 Performance Optimizations

We employ several optimization techniques: speculative execution on branch forks, lazy state materialization for historical queries, and checkpoint aggregation to reduce storage overhead.

Optimization Improvement Trade-off
Speculative Execution 3.2x throughput 2x memory usage
Lazy Materialization 5.1x faster queries Initial delay on access
Checkpoint Aggregation 82% storage reduction Longer finality time

5. Conclusion

CHRONA demonstrates that temporal programmability can be integrated into distributed systems without sacrificing consistency guarantees or performance characteristics. Our four-layer architecture provides clean abstractions for developers while maintaining Byzantine fault tolerance across parallel timeline execution.

Applications built on CHRONA exhibit novel capabilities: rewinding failed transactions, exploring alternative execution paths, and reconstructing historical state with perfect fidelity. These primitives enable entirely new classes of applications previously impossible in traditional blockchain architectures.

Future work includes extending temporal consensus to support cross-chain state coordination, implementing zero-knowledge proofs for private temporal operations, and exploring quantum-resistant cryptographic commitments for long-term state archival.

Acknowledgments

This work represents the synthesis of research across distributed systems, temporal logic, and Byzantine consensus protocols. We thank the broader research community for foundational work that made temporal compute layers possible.

Research Lab

Advancing the frontiers of temporal computation and distributed consensus.

The CHRONA Research Lab explores fundamental questions at the intersection of temporal logic, distributed systems, and cryptographic protocols. Our work spans theoretical foundations and practical implementations of time-based computation.

23
Publications
7
Research Areas
14
Collaborators
5
Open Problems

Current Focus Areas

Our research agenda encompasses both foundational theory and applied systems work:

Temporal Byzantine Fault Tolerance
Extending classical BFT to non-linear execution paths
Causal Consistency Models
Formalized semantics for temporal state transitions
Zero-Knowledge Temporal Proofs
Private verification of historical execution paths
Cross-Chain Temporal Bridges
State coordination across heterogeneous protocols

Temporal Logic Research

Formal foundations for reasoning about time in distributed systems.

Our temporal logic work extends classical Linear Temporal Logic (LTL) and Computational Tree Logic (CTL) to handle branching timelines and parallel execution paths.

Branching Time Semantics

We introduce Branch Temporal Logic (BTL), which adds operators for reasoning about timeline forks and merges:

φ ::= p | ¬φ | φ ∧ ψ | ◯φ | φ U ψ | ⑂φ | ⟲φ | ⟳φ

where ⑂φ = "φ holds on some branch"
⟲φ = "φ held at some past state"
⟳φ = "φ will hold after merge"

Verification Techniques

Model checking temporal properties across branching timelines presents unique challenges. We've developed specialized algorithms that exploit structural properties of timeline graphs to achieve tractable verification for real-world systems.

Consensus Theory

Byzantine agreement for non-linear state progression.

Traditional consensus protocols assume linear state histories. Our work extends these foundations to handle parallel execution with eventual convergence guarantees.

Safety and Liveness

We prove that temporal BFT maintains classical safety and liveness properties even under adversarial conditions where up to f < n/3 nodes behave maliciously.

Safety: ∀ branches b₁, b₂. commit(b₁) ∧ commit(b₂) → consistent(b₁, b₂)

Liveness: ∀ proposals p. eventually(commit(p) ∨ reject(p))

Convergence Proofs

Our merge protocols guarantee that all honest nodes converge to identical states regardless of message ordering or network partitions, provided eventual synchrony.

Application Domains

Real-world use cases enabled by temporal programmability.

Financial Systems

Trading platforms can simulate market conditions across parallel timelines, identifying optimal execution strategies before committing capital.

Gaming & Simulation

Multiplayer games gain the ability to explore alternative storylines, rewind failed attempts, and merge player-driven narratives.

Scientific Computing

Researchers can replay experiments with modified parameters, comparing outcomes across thousands of parallel execution paths.

Governance Systems

DAOs can simulate policy changes before implementation, understanding long-term implications through temporal projections.

Publications

Peer-reviewed research advancing temporal computation.

2025

Temporal Byzantine Fault Tolerance for Branching Histories
Proceedings of PODC 2025

Zero-Knowledge Proofs for Temporal State Transitions
Advances in Cryptology – CRYPTO 2025

2024

CHRONA: Decoupling Time from Block Height
ACM Symposium on Operating Systems Principles

Efficient State Capture in Distributed Systems
USENIX Annual Technical Conference

Causal Consistency for Parallel Timelines
IEEE International Conference on Distributed Computing Systems

Research Team

Advancing the science of temporal computation.

Our interdisciplinary team brings together expertise in distributed systems, temporal logic, cryptography, and formal verification.

Research positions are open for PhD candidates and postdoctoral researchers interested in foundational problems at the intersection of time and computation.

Request Access

CHRONA is opening access to select partners and researchers. Share your use case to join the waitlist.

For general inquiries: hello@chrona.network

Contact Us

Have questions about CHRONA? Our team is here to help.

Direct email: hello@chrona.network