Diamante Quantum White Paper

1. Abstract

Diamante unifies three execution paradigms - Type-3 zkEVM, enterprise Chaincode, and a native WASM VM (“DNA”) - over a hybrid consensus pipeline: PoH pre-ordering, DPoS validator election, and aBFT finality.

The network is designed to be post-quantum secure by default, adopting the NIST-standardized primitives:

ML-KEM (Kyber) for key exchange,
ML-DSA (Dilithium) for digital signatures, and
SLH-DSA (SPHINCS+) as an alternative where stateless signatures are operationally preferred.

A built-in confidentiality layer leverages succinct zero-knowledge proofs (zk-proofs) to enable:

Shielded assets (confidential transfers of value),
Private computations (executing logic without exposing inputs).

To ensure reproducibility and reliability in deployment, the design ships with:

A benchmarking suite (measuring TPS, latency, resource usage), and
SRE runbooks (validated operational guides for monitoring, scaling, incident recovery).

Expansion:

Diamante targets 100,000+ TPS with <1s finality. Early derivations (see Consensus section) show that with a block interval of T_block = 0.1s and average transaction size of 250B, the network requires ~24 MB/s sustained bandwidth per validator and ~2TB/day storage ingestion—numbers achievable on enterprise-grade NVMe + fiber networking.

2. Introduction

Diamante is engineered to address the twin challenges of:

Web-scale performance - ensuring throughput comparable to high-frequency trading systems or global payment rails.
Long-term cryptographic resilience - ensuring safety against adversaries equipped with large-scale quantum computers.

Its architecture emphasizes:

Modularity - Execution VMs, consensus, storage, and confidentiality are pluggable.
Developer onboarding - Familiar toolchains (Solidity, Go, Rust, Java, WASM).
Deployability - Optimized for both server-class hardware (NVMe + multicore) and mobile devices (light clients with zk-proof verification).

2.1 Motivation

Quantum resilience:

Diamante integrates post-quantum cryptography (PQC) as protocol defaults, not as optional add-ons.
Security baseline: adversary model assumes Shor’s algorithm is practical within the system’s lifetime.
Mathematical note: With n validators and a target of f_max = floor((n-1)/3) Byzantine tolerance, if signatures are broken by quantum adversaries, f > f_max could collapse safety. Thus PQC defaults protect validator integrity.

Performance at scale:

Sub-second finality is achieved by pipelined consensus: PoH reduces ordering latency, DPoS accelerates proposer selection, and aBFT ensures strong safety.
Numeric example:

TTF≤Tpoh+R⋅Δ+TexecTTF \leq T_{poh} + R \cdot \Delta + T_{exec}TTF≤Tpoh +R⋅Δ+Texec   

For T_poh = 0.010s, R = 3, Δ = 0.1s, T_exec = 0.005s: 

TTF=0.315sTTF = 0.315sTTF=0.315s

⇒ comfortably below 1 second.

Multi-paradigm flexibility:

zkEVM: full Solidity/Ethereum compatibility with zk-rollup proof validation.
Chaincode: enterprise developers (Go, Java, Node.js).
DNA (WASM): performance, multi-language support (Rust, C++, AssemblyScript)

2.2 Vision

Diamante envisions a single interoperable network where:

Cross-VM atomicity: Contracts from zkEVM, Chaincode, and WASM interoperate atomically.
Privacy-first: Confidentiality is a native feature (not a bolt-on).
Operational excellence: SREs and validators operate with strict SLOs (latency, throughput, uptime) backed by reproducible metrics.

3. Architectural Design

3.1 Network Infrastructure

A secure peer-to-peer (P2P) overlay forms the backbone of Diamante’s communication fabric.

It integrates:

TLS (Transport Layer Security) for encryption-in-transit,
Rate limiting to mitigate denial-of-service vectors, and
Partition handling to ensure safety under partial synchrony conditions.

Service Layer Exposure:

Nodes provide REST/gRPC endpoints for wallet integration, explorer queries, and bulk operations (e.g., exchanges ingesting large block ranges).
A service mesh abstraction standardizes observability, authentication, and access control.

Observability:

Metrics (Prometheus/Grafana), logs, and distributed traces (OpenTelemetry) are integrated directly at the protocol layer.
Security surfaces include anomaly detection (e.g., sudden peer churn, replayed transactions).

Numerical Derivation - Bandwidth per Node

Each validator must sustain network traffic proportional to TPS × transaction size.

BWnode=TPS×avg_tx_size10242 MB/sBW_{node} = \frac{TPS \times avg\_tx\_size}{1024^2} \; MB/sBWnode =10242TPS×avg_tx_size MB/s

Example:

TPS = 100,000
avg_tx_size = 250 B

BWnode=100,000×25010242≈23.84  MB/s  (≈190  Mbps)BW_{node} = \frac{100,000 \times 250}{1024^2} ≈ 23.84 \; MB/s \; (\approx 190 \; Mbps)BWnode =10242100,000×250 ≈23.84MB/s(≈190Mbps)

Thus, a validator must support ≥200 Mbps sustained throughput, aligning with datacenter-grade fiber.

Numerical Derivation - Validator Connectivity

For n validators, each must gossip block proposals and votes. Assuming full broadcast:

Messages per block ≈n×(votes+proposals)Messages \; per \; block \; \approx n \times (votes + proposals)Messagesperblock≈n×(votes+proposals)

If n = 100, each block incurs ~100 votes + 1 proposal. At T_block = 0.1s, this yields:

100×10 blocks/s=1,000 vote msgs/s100 \times 10 \; blocks/s = 1,000 \; vote \; msgs/s100×10blocks/s=1,000votemsgs/s

Each ~200B → 200 KB/s overhead, negligible compared to transaction payloads.

Network Diagram:

3.2 Multi-Layer Consensus Mechanism

Diamante leverages a hybrid consensus architecture, combining PoH (Proof of History), DPoS (Delegated Proof of Stake), and aBFT (asynchronous Byzantine Fault Tolerance) to achieve high throughput, low latency, and deterministic finality.

Proof of History (PoH) (Pre‑Ordering)

Concept:

PoH uses a verifiable hash chain to timestamp transactions before they enter the consensus process. This allows nodes to have a globally agreed order without waiting for a full consensus, reducing contention for block finality.

Mathematical Formulation:

Let the hash chain be defined recursively as:

H0=initial seed,Hk=hash(Hk−1)H_0 = \text{initial seed}, \quad H_k = \text{hash}(H_{k-1})H0 =initial seed,Hk =hash(Hk−1 )

A transaction tx inserted at step k carries proof of its position:

PoH Proof(tx)=Hk\text{PoH Proof}(tx) = H_kPoH Proof(tx)=Hk

This ensures auditable timing and that the sequence of events is verifiable independently.

Example:

Transaction A: inserted at H_1000
Transaction B: inserted at H_1005 Observers know A definitely came before B without waiting for DPoS/aBFT validation.

Delegated Proof of Stake (DPoS) (Election / Proposal)

Concept:

Staked token holders vote to elect a finite set of validators for each epoch. Validators propose and order blocks based on PoH sequences.

Mathematical Derivation:

Let validator i have stake SiS_iSi
Total network stake: ΣjSj\Sigma_j S_jΣj Sj

The probability that validator i is selected to propose a block:

P(Vi)=Si∑jSjP(V_i) = \frac{S_i}{\sum_j S_j}P(Vi )=∑j Sj Si

Over an epoch of BBB blocks, the expected number of blocks proposed by validator i:

E[Bi]=P(Vi)⋅B=Si∑jSj⋅BE[B_i] = P(V_i) \cdot B = \frac{S_i}{\sum_j S_j} \cdot BE[Bi ]=P(Vi )⋅B=∑j Sj Si ⋅B

Example:

Total stake = 1000 tokens
Validator A stake = 200 tokens
Epoch = 50 blocks

E[BA]=2001000⋅50=10 blocks expectedE[B_A] = \frac{200}{1000} \cdot 50 = 10 \text{ blocks expected}E[BA ]=1000200 ⋅50=10 blocks expected

Asynchronous Byzantine Fault Tolerance (aBFT) (Finality)

Concept:

Provides deterministic finality when the number of Byzantine (malicious) nodes f<⌊n/3⌋f < \lfloor n/3 \rfloorf<⌊n/3⌋, where nnn is total validators. This ensures safety and liveness even under partial network failures.

Safety Condition: f<⌊n/3⌋f < \lfloor n/3 \rfloorf<⌊n/3⌋
Finality Guarantee: Once aBFT confirms a block, it is irreversible.

Latency & Throughput

To estimate Time-to-Finality (TTF) and Transactions per Second (TPS):

Time-to-Finality (TTF):

TTF≲Tpoh+R⋅Δ+TexecTTF \lesssim T_{\text{poh}} + R \cdot \Delta + T_{\text{exec}}TTF≲Tpoh +R⋅Δ+Texec

Where:

TpohT_{\text{poh}}Tpoh = PoH queueing time
RRR = number of aBFT rounds
Δ\DeltaΔ = network delay bound under partial synchrony
TexecT_{\text{exec}}Texec = transaction execution time

Throughput (TPS):

TPS≈B−ϵs^⋅1TblockTPS \approx \frac{B - \epsilon}{\hat{s}} \cdot \frac{1}{T_{\text{block}}}TPS≈s^B−ϵ ⋅Tblock 1

Where:

BBB = transactions per block
ϵ\epsilonϵ = overhead for block metadata / verification
s^\hat{s}s^ = average transaction size
TblockT_{\text{block}}Tblock = average block time

Throughput is bounded by per-node capacities such as:

Signature or zero-knowledge verification speed
Network bandwidth
VM execution speed

Example Calculation:

Assume: 
B=1000B = 1000B=1000 tx/block 
ϵ=50\epsilon = 50ϵ=50 tx 
s^=1\hat{s} = 1s^=1 tx size unit 
Tblock=0.5T_{\text{block}} = 0.5Tblock =0.5 sec

TPS≈1000−501⋅10.5=950⋅2=1900 TPSTPS \approx \frac{1000-50}{1} \cdot \frac{1}{0.5} = 950 \cdot 2 = 1900 \text{ TPS}TPS≈11000−50 ⋅0.51 =950⋅2=1900 TPS

4. Post -Quantum Cryptography Baseline

Diamante is designed to resist quantum attacks by using post-quantum cryptographic primitives for key exchange, signatures, and stateless signing.

ML‑KEM (Kyber) - Lattice-based key encapsulation for secure key exchange. The sender encapsulates a symmetric key using the receiver’s public key, and the receiver decapsulates it to recover the same key. Quantum-resistant and efficient.
ML‑DSA (Dilithium) - Lattice-based digital signatures for authenticating transactions and blocks. Deterministic and fast, ensuring message integrity and non-repudiation.
SLH‑DSA (SPHINCS+) - Stateless hash-based signatures for contexts where private key state tracking is difficult, such as lightweight wallets or ephemeral signatures. Resistant to quantum attacks without the risk of double-signing.

Implementation Notes:

All primitives follow FIPS errata and documented provider versions for compliance, security, and auditability.

5.Unified Smart-Contract Stack

Diamante provides a multi-paradigm smart-contract environment, allowing developers to write contracts in Solidity/Vyper, Chaincode, or a resource-oriented WASM language (DNA), all while maintaining atomic interoperability across these layers.

5.1 Type-3zkEVM

Concept:

Type‑3 zkEVM provides bytecode-level compatibility with Ethereum, meaning that existing Solidity and Vyper contracts can run without modification. It also integrates seamlessly with developer tools like Foundry, Hardhat, and MetaMask.

Key Features:

Supports zero-knowledge proofs for privacy and succinct verification.
Enables layer‑1 privacy for dApps by verifying execution off-chain while committing proofs on-chain.

Example / Derivation:

Solidity contract:

function transfer(address to, uint256 amount) public { balance[msg.sender] -= amount; balance[to] += amount; }

zkEVM execution produces a zk-proof π verifying that balances are updated correctly without revealing intermediary state:

π=zkProve(statebefore,tx,stateafter)\pi = \text{zkProve}(\text{state}_{\text{before}}, \text{tx}, \text{state}_{\text{after}})π=zkProve(statebefore ,tx,stateafter )

Nodes verify π on-chain instead of replaying the transaction:

Verify(π,statebefore,stateafter)=true\text{Verify}(\pi, \text{state}_{\text{before}}, \text{state}_{\text{after}}) = \text{true}Verify(π,statebefore ,stateafter )=true

5.2 Enterprise Chaincode

Concept:

Chaincode is a sandboxed execution environment for business logic, supporting Go, Java, or Node.js. Designed for enterprise-grade applications, it ensures auditability through on-chain proofs and hashes.

Key Features:

Contracts execute off-chain but commit hashes of state changes on-chain for verification.
Privacy for business data is preserved without sacrificing regulatory auditability.

Example / Derivation:

A supply-chain Chaincode in Go updates shipment status:

shipment.Status = "Delivered" hash := SHA256(shipment) CommitHashToChain(hash)

The hash allows auditors to verify authenticity without exposing sensitive data.

5.3 DNA-Native WASM & Resource Semantics

Concept:

DNA is a resource-oriented language compiled to WebAssembly (WASM). It enforces ownership and linearity, preventing accidental duplication or dropping of assets at compile-time, eliminating a whole class of runtime bugs.

Key Features:

Linear types: Each asset must be used exactly once.
Ownership semantics: Prevents unauthorized access or implicit copies.

Example / Derivation:

resource Coin { value: u64 } fn transfer(from: &mut Coin, to: &mut Coin) { let tmp = move(from); // linear move deposit(to, tmp); }

Here, the compiler enforces that from is consumed exactly once, ensuring no coins are duplicated or lost.

5.4 CVM - Cross-VM Atomic Calls

Concept:

The Cross-VM Messaging (CVM) system allows atomic interactions across different execution layers (zkEVM, DNA, Chaincode).

Key Features:

Ordered, asynchronous message bus.
Atomicity: Either the entire multi-VM transaction succeeds or the system reverts globally.

Example / Derivation:

Composite call: zkEVM → DNA → Chaincode

CompositeCall=atomic(txzkEVM,txDNA,txChaincode)\text{CompositeCall} = \text{atomic}(tx_{\text{zkEVM}}, tx_{\text{DNA}}, tx_{\text{Chaincode}})CompositeCall=atomic(txzkEVM ,txDNA ,txChaincode )

If tx_DNA fails, all preceding steps revert, ensuring no partial state:

Commit(CompositeCall) ⟹ all-or-nothing\text{Commit}(\text{CompositeCall}) \implies \text{all-or-nothing}Commit(CompositeCall)⟹all-or-nothing

This guarantees consistency and integrity across multiple smart-contract paradigms.

zkEVM → Ethereum-compatible contracts with zk-proofs
DNA → Resource-safe native WASM contracts
Chaincode → Private business logic with auditable state

6. Confidentiality Layer

Diamante provides transactional privacy and confidentiality using zero-knowledge cryptography and commitment schemes. This ensures that transaction data, balances, and ownership are hidden, while correctness can still be verified on-chain.

6.1 Commitment/Nullifier Model

Concept:

Shielded transfers hide who sent what to whom. This is achieved with:

Commitments: Cryptographic constructs that hide the value and owner of an asset while still allowing proofs about it.
Nullifiers: Unique identifiers that prevent double-spending by marking commitments as “spent” without revealing which commitment it was.

How it works (simplified):

Sender creates a commitment for a transaction:

C=Commit(v,r,pk)C = \text{Commit}(v, r, pk)C=Commit(v,r,pk)

where vvv = value, rrr = randomness, pkpkpk = recipient’s public key.

Sender generates a zero-knowledge proof that:
They own the committed asset
The output values sum correctly
They are not double-spending
On-chain storage: Only the commitments, nullifiers, and zk-proofs are published, never actual amounts or identities.

Example:

Alice wants to send 50 DIAM to Bob privately.
Generates commitment CAC_ACA and proof π\piπ.
On-chain: Commitments = C_A, Nullifiers = N_A, Proof = π
Network nodes verify correctness without seeing the actual 50 DIAM.

6.2 zk-Proof Systems & Polynomial Commitments

Concept:

Diamante uses succinct zero-knowledge proofs (SNARKs/STARKs) for privacy-preserving computation, with polynomial commitments to represent data efficiently.

KZG (Kate-Zaverucha-Goldberg) commitments over BLS12-381 curve are commonly used.
These allow a verifier to check that a polynomial f(x)f(x)f(x) evaluates correctly at a point without knowing the whole polynomial.

// Mathematical Check: 
Let CCC be a commitment to polynomial fff: 
C=g1f(τ)C = g_1^{f(\tau)}C=g1f(τ)   
Verifier wants to check that f(x)=yf(x) = yf(x)=y using proof π\piπ: 
e(Cg1y,g2)=?e(π,g2τ−x)e\left(\frac{C}{g_1^y}, g_2\right) \stackrel{?}{=} e(\pi, g_2^{\tau - x})e(g1y C ,g2 )=?e(π,g2τ−x )  
Where: 
eee = pairing function 
g1,g2g_1, g_2g1 ,g2  = elliptic curve generators 
τ\tauτ = secret trapdoor known only to prover

Explanation:

The verifier doesn’t see the polynomial itself, only the commitment CCC and the proof π\piπ.
If the equality holds, the polynomial evaluates correctly at the given point.

Quantum Consideration:

Pairing-based SNARKs (like KZG/BLS12-381) are not quantum-safe.
For post-quantum security, Diamante can use STARK backends, which rely on hash-based constructions instead of pairings.

Diamante enables transparent and traceable operations within supply chains, ensuring authenticity and accountability.

7. Distributed State & Storage Architecture

Diamante uses a tiered storage architecture to balance performance, consistency, and accessibility:

LMDB: Stores the canonical blockchain state (ACID, MVCC, memory-mapped) for reliable transaction finality.
Redis: In-memory cache for hot keys and low-latency lookups, reducing load on LMDB.
MongoDB: Archival storage for analytics and historical queries with sharding support.
SQLite: Lightweight, embedded storage for mobile/edge clients, enabling offline or resource-constrained access.

Intuition: LMDB = source of truth, Redis = speed layer, MongoDB = historical/analytics layer, SQLite = edge snapshot.

8. Network, API & Runtime Architecture

Diamante’s architecture integrates networking, APIs, and execution runtimes to provide secure, scalable, and observable blockchain operations.

Network Layer

Concept:

P2P network: Nodes communicate peer-to-peer to propagate transactions and blocks.
TLS-secured transport: Ensures encryption and authentication of all messages.
Partition handling: Handles network splits and reconnections to maintain eventual consistency.

Example / Notes:

During a network partition, validators may temporarily see different states, but reconciliation ensures convergent finality once connectivity restores.

API Layer

Concept:

Provides REST and gRPC interfaces for wallet operations, transactions, and bulk operations.
Enables external applications and services to interact with the blockchain in a standardized and secure manner.

Example / Notes:

Wallet API call: POST /transaction/send → creates transaction → network propagates via P2P.
Bulk API call: POST /transactions/batch → optimized for high-throughput operations without overloading nodes.

Runtime Layer

Concept:

Supports three execution environments:
EVM / zkEVM – Ethereum-compatible smart contracts
WASM / DNA – Resource-oriented, safe native contracts
Chaincode – Enterprise sandboxed logic
Observability & security integrated end-to-end: logs, metrics, tracing, and runtime access controls.

Example / Notes:

Transaction execution:
Input arrives via API
Routed to appropriate runtime (EVM, DNA, or Chaincode)
State updates committed to LMDB and caches, audit logs recorded
Cross-VM atomicity (via CVM) ensures consistency when calls span multiple runtimes.

9. Governance & Token Utility

Diamante’s native token, $DIAM, serves multiple purposes:

Fees: Used to pay for transaction execution, storage, and computation.
Example: Sending 100 DIAM from Alice to Bob incurs a fee of 0.1 DIAM per transaction, deducted from Alice’s balance.
Staking: Validators lock $DIAM to participate in DPoS elections and secure the network.
Probability of selection derivation: If validator i stakes SiS_iSi and total stake is ∑jSj\sum_j S_j∑j Sj :

P(Vi)=Si∑jSjP(V_i) = \frac{S_i}{\sum_j S_j}P(Vi )=∑j Sj Si

Example:

Total stake = 1000 DIAM
Validator A stake = 200 DIAM
Probability of being selected: P(VA)=200/1000=0.2P(V_A) = 200/1000 = 0.2P(VA )=200/1000=0.2 → expects to propose ~20% of blocks.
Governance: On-chain governance allows proposal submission, voting, and enactment.

Mechanism:

Users submit deposit-gated proposals.
Voting uses token-weighted delegation.
Proposals require quorum/threshold to pass.
Enactment occurs after a time-lock period to allow review or dispute.

Example:

Proposal requires 10,000 DIAM voting power to pass
Alice delegates 500 DIAM to Validator B → Validator B votes with Alice’s weight
Proposal passes if sum of delegated + self-staked votes ≥ threshold
Collateral: $DIAM can be locked as collateral for on-chain protocols, DeFi applications, or Layer‑2 interactions.

Example:

A user locks 100 DIAM as collateral to mint a stablecoin or participate in a liquidity pool.

10. Performance Benchmarks & Research Methodology

Diamante uses a comprehensive benchmarking suite to evaluate transaction throughput, consensus efficiency, and storage performance, ensuring the network meets high-performance targets.

Benchmarking Metrics

Transactions per Second (TPS): Measures how many transactions the network can process per second.
Target: ≥ 100,000 TPS

Example / Derivation:

Suppose a block contains B=500B = 500B=500 transactions and blocks are produced every Tblock=5T_{\text{block}} = 5Tblock =5 ms:

TPS=BTblock=5000.005=100,000TPS = \frac{B}{T_{\text{block}}} = \frac{500}{0.005} = 100,000TPS=Tblock B =0.005500 =100,000

This matches the target throughput.
Latency Percentiles: Measures transaction processing delays across the network.
P50, P90, P95, P99 indicate median and worst-case response times.
Target: P99 ≤ 10 ms
Example: If 10,000 sample transactions are measured, the 99th percentile is the transaction with the second-highest latency out of 10,000.
Resource Profiling: Measures memory and CPU usage.
Targets: Memory ≤ 2 GB, CPU ≤ 80%
Ensures nodes can run efficiently without overloading hardware.

Benchmarking Outputs:

Machine-readable: report.json containing metrics such as TPS, latencies, and variance.
Human-readable: Summaries with pass/fail indicators for each target metric.

Example Report Snippet:

{ 
 "TPS": 102345, 
 "Latency": {"P50": 3.2, "P90": 5.8, "P95": 7.1, "P99": 9.8}, 
 "Memory_GB": 1.9, 
 "CPU_percent": 72, 
 "Pass": true 
}

Statistical treatment:

Measures variance and error breakdowns to assess network stability.
Example: If TPS fluctuates heavily across runs, variance indicates reliability concerns.

11. Validator Operations & SRE Playbooks

Diamante provides structured playbooks for validators and SREs to ensure network reliability, security, and performance.

Operations Playbooks

Purpose: Standardize routine tasks and emergency procedures.

Daily/Weekly/Monthly Routines:

Check node health, sync status, peer connectivity, and log errors.
Perform backups, update monitoring dashboards, and review alerts.

Monitoring & Observability:

Prometheus/Grafana dashboards track uptime, block production, CPU/memory usage, and peer count.
Alerts configured for critical conditions:
Node jailed or offline
Missed blocks
Low peer connectivity

Example:

If a validator misses 12 blocks in a day, an alert triggers since SLOs specify missed blocks < 10/day.

Security & Maintenance:

Routine security hardening, OS updates, and node maintenance.
Upgrades/migrations follow stepwise procedures with rollback plans.
Emergency response guides cover network partition, failed nodes, or compromised keys.

Service Level Objectives (SLOs):

Validators aim to maintain network stability and performance with measurable SLOs:

Metric

Target

Example

Uptime

> 99%

Node online 99% of the month

Missed Blocks

< 10/day (warn > 50/day)

Alert triggers if validator misses 12 blocks

Resource Usage

Memory/CPU/Disk < 80%

Node uses 70% CPU → healthy

Peer Count

> 10

Node drops to 8 peers → alert

Example / Derivation:

Missed Blocks:
Expected blocks/day: 7200 (if 10 s block time)
Threshold: 10 → 0.14% tolerance
Alerts trigger if exceeded → helps maintain validator reliability.
Uptime:

Uptime %=Time onlineTotal time×100\text{Uptime \%} = \frac{\text{Time online}}{\text{Total time}} \times 100Uptime %=Total timeTime online ×100

Example: Node online 29.8/30 days → 29.8/30×100≈99.3%29.8/30 \times 100 \approx 99.3\%29.8/30×100≈99.3% → meets SLO.

12. Security Analysis & Formal Properties

Diamante’s security is analyzed across safety, liveness, cryptography, and privacy to ensure the network is robust, verifiable, and resistant to attacks.

1. Safety

Concept:

Safety guarantees that conflicting finalizations cannot occur unless a threshold of validators behave maliciously.

Formal Condition:

n≥3f+1n \ge 3f + 1n≥3f+1

Where:

nnn = total validators
fff = maximum Byzantine (malicious) validators

Example / Derivation:

Total validators n=100n = 100n=100 → maximum tolerated Byzantine f=⌊(100−1)/3⌋=33f = \lfloor (100-1)/3 \rfloor = 33f=⌊(100−1)/3⌋=33
To finalize two conflicting blocks, at least one honest validator would need to double-vote.
Slashing ensures that any misbehavior leads to economic penalty, deterring double-voting.

2. Liveness

Concept:

Liveness ensures that transactions and proposals eventually finalize, even under partial network delays.

Formal Condition:

Network has partial synchrony: eventual message delivery within bound Δ\DeltaΔ.
After a finite number of rounds RRR, proposals reach finality.

Example:

Suppose Δ=100\Delta = 100Δ=100 ms, and aBFT protocol uses 3 rounds → any valid proposal finalizes in ≤ 3 × 100 ms = 300 ms (ignoring execution time).

3. Cryptography

Concept:

Diamante uses a post-quantum cryptography (PQC) baseline (see §3).

PQC primitives ensure key exchange and signatures are quantum-resistant.
Pairing-based SNARKs (e.g., KZG/BLS12-381) are not quantum-safe.
STARK-based proofs are considered when post-quantum security is required, relying on hash-based constructions rather than elliptic curve pairings.

4. Privacy

Concept:

Uses commitment/nullifier model to provide transaction confidentiality.
Soundness: Proofs ensure correct execution without revealing hidden values.
Unlinkability: Observers cannot link inputs to outputs.

Example / Derivation:

Alice sends 50 DIAM to Bob:
Commitment C=Commit(50,r,pkB)C = \text{Commit}(50, r, pk_B)C=Commit(50,r,pkB )
Nullifier NNN prevents double-spending
zk-proof π\piπ verifies correctness without revealing amount or parties.
Even if network observes CCC and NNN, they cannot determine the sender, receiver, or value.

13. Interoperability & Standards Alignment

Diamante is designed to interoperate both within its own multi-paradigm stack and externally with other chains, while aligning with industry standards.

1. Intra‑Chain Interoperability

Concept:

The Cross-VM Messaging (CVM) system enables atomic operations across multiple VMs (zkEVM, DNA/WASM, Chaincode) within a single consensus domain.
Ensures ordered execution, capability checks, and atomic commits.

Example / Derivation:

Suppose a composite transaction spans three VMs:

zkEVM transfers token to a DNA contract
DNA contract triggers a Chaincode operation
Chaincode updates enterprise ledger

Atomicity is enforced:

CompositeCall=atomic(txzkEVM,txDNA,txChaincode)\text{CompositeCall} = \text{atomic}(tx_{\text{zkEVM}}, tx_{\text{DNA}}, tx_{\text{Chaincode}})CompositeCall=atomic(txzkEVM ,txDNA ,txChaincode )

If any step fails, the entire transaction sequence reverts, ensuring consistency across VMs.

2. Extra‑Chain Interoperability

Concept:

Bridges and relayers enable communication with external chains.
Uses proof adapters and light-client verifiers to validate external chain states safely.

Example / Notes:

A Diamante token is locked in a bridge contract.
Proof of the lock (e.g., a zk-proof or Merkle proof) is relayed to Ethereum.
Light-client verifier on Diamante confirms the proof → tokens are minted or unlocked on the other chain.

Roadmap:

Integration with existing standards for cross-chain messaging, token wrapping, and proofs ensures secure interoperability while preserving Diamante’s atomicity and privacy guarantees.

14. Conclusion

Diamante is a next-generation blockchain protocol that unifies multiple execution paradigms—zkEVM, DNA/WASM, and enterprise Chaincode—within a single platform. By leveraging a hybrid consensus pipeline of PoH pre-ordering, DPoS elections, and aBFT finality, the network achieves high throughput, sub-second finality, and robust security even in the presence of Byzantine actors. Its post-quantum cryptography baseline and integrated privacy mechanisms, including commitments, nullifiers, and zero-knowledge proofs, ensure secure, confidential, and verifiable transactions without compromising efficiency. The tiered storage architecture, spanning LMDB, Redis, MongoDB, and SQLite, balances performance, reliability, and accessibility for full nodes and edge clients alike.

From an operational and developer perspective, Diamante provides SRE playbooks, observability dashboards, alerting rules, and governance frameworks to maintain uptime, validator performance, and network stability. The $DIAM token powers fees, staking, governance, and collateral, aligning economic incentives with security and decentralization. Combined with Cross-VM atomicity, intra- and extra-chain interoperability, and developer-friendly APIs and tooling, Diamante delivers a scalable, privacy-conscious, and enterprise-ready ecosystem, capable of supporting web-scale applications and complex multi-paradigm smart contracts.

Contributors

Diamante Research Lab Team

Suryakanta Mahanty, Technology Group Head. Diamante

Calvin Joshua, Blockchain Lead, Diamante

Apoorv Kulshestra, Blockchain Lead, Diamante

Reviewer

Arijit Biswas, Chief Technical Officer, Diamante

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Table Of Contents

1. Abstract

2. Introduction

2.1 Motivation

2.2 Vision

3. Architectural Design

3.1 Network Infrastructure

Network Diagram:

3.2 Multi-Layer Consensus Mechanism

4. Post -Quantum Cryptography Baseline

5.Unified Smart-Contract Stack

5.1 Type-3zkEVM

5.2 Enterprise Chaincode

5.3 DNA-Native WASM & Resource Semantics

5.4 CVM - Cross-VM Atomic Calls

6. Confidentiality Layer

6.1 Commitment/Nullifier Model

6.2 zk-Proof Systems & Polynomial Commitments

7. Distributed State & Storage Architecture

8. Network, API & Runtime Architecture

9. Governance & Token Utility

10. Performance Benchmarks & Research Methodology

11. Validator Operations & SRE Playbooks

12. Security Analysis & Formal Properties

13. Interoperability & Standards Alignment

14. Conclusion