DsecOS Enterprise

Qiskit Simulation Environment for Quantum Computing Tests

Harness Quantum Algorithms in a Classical, Isolated Environment

Secure R&D Cost-Effective Scalable Export Controlled

2

Platform Overview

A secure platform for a Qiskit-based quantum simulation environment, enabling developers and researchers to test quantum circuits, algorithms (e.g., Shor's, Grover's), and error mitigation strategies without access to physical quantum hardware. Qiskit, IBM's open-source quantum SDK, runs in a hardened containerized setup, simulating noisy quantum systems for deployment validation.

Cost Savings

$10K/hr

Vs. quantum cloud

Qubit Simulation

100+

On classical hardware

Deployment Time

<10 min

Per node

IP Protection

100%

SELinux confined

                Business Value
                Cost-Effective Testing: Simulate 100+ qubits on classical hardware vs. $10K/hour quantum cloud access
Secure Development: SELinux confines simulations to prevent IP leakage
Scalability: Parallelize simulations across Ceph-distributed storage
Integration Ready: Export results to real quantum providers (e.g., IBM Quantum) via API

            

⚡ Ideal For: Quantum computing R&D teams in pharmaceuticals (drug discovery), finance (portfolio optimization), or logistics (routing optimization)

3

Technical Foundation

Component	Role	Security Features
Qiskit + Aer Simulator	Circuit design, noise modeling, up to 32-qubit simulations	Rootless Python env, AppArmor, seccomp filters
JupyterLab Interface	Interactive notebook for algorithm testing	JWT auth, rate-limited access, encrypted sessions
PostgreSQL Backend	Store circuit results, error rates	LUKS-encrypted, row-level security for proprietary data
AI Optimizer	Auto-tune error mitigation (e.g., dynamical decoupling)	ML models trained on simulation logs

                Platform Security
                Kernel Security: SELinux policies for qiskit_t domain, restricting simulator access
Resource Isolation: LXC containers with dedicated vCPUs/GPUs for parallel Aer simulations
Storage: Ceph for distributed quantum state vectors (up to 2^50 amplitudes)
Networking: Zero-trust SDN isolates simulation traffic from classical apps

            

4

Cluster Architecture

5-Node Cluster (On-Prem Lab or Hybrid with AWS)

graph TD subgraph "DsecOS Enterprise Cluster (5 Nodes)" N1[DsecOS Node 1
Master + Ceph MON] N2[DsecOS Node 2
Qiskit Simulator + GPU] N3[DsecOS Node 3
JupyterLab Gateway] N4[DsecOS Node 4
Worker + Ceph OSD] N5[DsecOS Node 5
AI Optimizer + Ceph OSD] end subgraph "Quantum Simulation Layer" QIS["Qiskit Core
(Circuit Builder)"] AER["Aer Simulator
(Noisy Backend)"] JUP["JupyterLab
(Interactive Notebooks)"] end subgraph "Data & Security" DB["PostgreSQL
(Results + Logs)"] AI["AI Error Mitigator
(Scikit + Qiskit)"] LIC[License Server
Enterprise JWT] end N1 <-->|Corosync HA| N2 N2 <--> N3 N3 <--> N4 N4 <--> N5 N1 --> CEPH[Ceph Cluster
Distributed State Storage] QIS --> N2 AER --> N2 JUP --> N3 DB --> N4 AI --> N5 CEPH --> QIS CEPH --> DB CEPH --> AI AI --> QIS LIC --> N1 style N1 fill:#121212,stroke:#9370db,color:#FFF style QIS fill:#1E1E1E,stroke:#9370db,color:#FFF style AI fill:#8B0000,color:#FFF

5

Simulation Deployment Flow

journey title Qiskit Simulation Deployment Flow section Provisioning Activate Enterprise License: 5: Quantum Researcher PXE Deploy 5 Nodes: 5: DevOps Configure GPU Passthrough: 4: Auto-Via Ansible section Development Launch JupyterLab: 5: React UI Design Grover's Circuit: 5: Notebook Run 28-Qubit Simulation: 4: Aer Backend section Testing Apply Noise Model: 5: One-Click Analyze Error Rates: 4: AI Insights Export to IBM Quantum: 3: API Call section Optimization Auto-Mitigate Errors: 3: ML-Driven Scale to 5 Nodes: 4: Load Balancer Generate Compliance Log: 5: Audit Export

6

Deployment Requirements

⚡ Prerequisites: DsecOS Enterprise license (quantum edition add-on), 5x servers (64 GB RAM, NVIDIA A100 GPUs, 2 TB SSD), high-bandwidth LAN

Step 1: Provision Nodes

# On provisioning server
/scripts/pxe-deploy.sh --cluster quantum-sim --nodes 5 --gpu-passthrough

Step 2: Activate License

In Web UI: Settings > License → Enter key. Enable quantum features (GPU isolation, large memory pools).

Step 3: Deploy Custom Stack

Create /templates/stacks/qiskit-sim.yml:

version: '3.8'
services:
  qiskit:
    image: mcr.microsoft.com/quantum/qiskit:latest
    working_dir: /workspace
    volumes:
      - ceph-quantum:/workspace
      - /dev/nvidia0:/dev/nvidia0
    environment:
      - QISKIT_SIMULATOR=AerSimulator
      - CUDA_VISIBLE_DEVICES=0
    command: jupyter lab --ip=0.0.0.0 --allow-root --no-browser
    ports:
      - "8888:8888"
    depends_on:
      - db

  db:
    image: postgres:16-alpine
    environment:
      POSTGRES_DB: qiskit_results
      POSTGRES_PASSWORD: quantum_secure
    volumes:
      - ceph-db:/var/lib/postgresql/data

  ai-optimizer:
    image: python:3.12-slim
    volumes:
      - ceph-ai:/models
    command: python /app/optimize_errors.py
    depends_on:
      - qiskit

volumes:
  ceph-quantum:
    driver: cephfs
  ceph-db:
    driver: cephfs
  ceph-ai:
    driver: cephfs

Deploy Command

dsecos deploy qiskit-sim

7

Run a Sample Simulation

In JupyterLab (http://your-ip:8888):

from qiskit import QuantumCircuit, Aer, execute
from qiskit.visualization import plot_histogram

# Grover's search on 3 qubits
qc = QuantumCircuit(3, 3)
qc.h([0, 1, 2])  # Superposition
qc.cz(0, 1)      # Oracle
qc.measure([0,1,2], [0,1,2])

simulator = Aer.get_backend('aer_simulator')
result = execute(qc, simulator, shots=1024).result()
counts = result.get_counts(qc)
plot_histogram(counts)

                Results
                Results Stored: In PostgreSQL with full audit trail
AI Analysis: Analyzes for fidelity >95%
Export Ready: Integration with IBM Quantum via secure API

            

8

Security & Compliance

Algorithm Protection

SELinux

Prevents exfiltration

Error Analysis

97%

AI detection accuracy

Compliance

NIST

Quantum-safe crypto

Export Control

100%

Sensitive algorithms

                Security Features
                Algorithm Protection: SELinux prevents exfiltration of quantum circuits
Error Analysis: AI detects simulation biases with 97% accuracy
Compliance: Logs for NIST quantum-safe crypto audits
Export Controls: Compliance with regulations on sensitive algorithms

            

9

Performance Metrics

Metric	Value
Qubit Simulation (28-qubit)	45 seconds (GPU)
Memory Usage (50-qubit)	128 GB (distributed Ceph)
Error Mitigation Speed	<10 seconds per circuit
Fidelity Improvement	+15% via dynamical decoupling

45s

28-Qubit

128GB

50-Qubit

+15%

Fidelity

<10s

Mitigation

10

Return on Investment

                Quantum R&D Lab Example (500 Simulations/Month)
                
                            Category
                            Current Costs
                            With DsecOS
                            Savings
                        
                            Annual Operating Costs
                            $200,000
                            $50,000
                            $150,000
                        
                            Iteration Speed
                            Baseline
                            5x faster
                            Accelerated

Category	Current Costs	With DsecOS	Savings
Annual Operating Costs	$200,000	$50,000	$150,000
Iteration Speed	Baseline	5x faster	Accelerated

Total Annual Savings

$150,000+

Plus 5x faster iteration

Simulating the Quantum Future, Secured in the Classical World

100+

Qubits

$150K

Savings

5x

Faster

100%

Secure

"Harness Quantum Algorithms in a Classical, Isolated Environment"

SECURE SCALABLE COST-EFFECTIVE EXPORT CONTROLLED

DsecOS Enterprise Quantum Edition