The simulator
Execute Large-Scale Quantum Circuits on Your Own Classical Systems
Simulate circuits that used to demand a supercomputer — right on your own machine, with near-perfect fidelity and no lock-in.
- Hundreds of qubits
- Millions of operations
- Near-perfect fidelity
- Free for non-commercial use
Why simulate
Real QPUs vs. Quantum Rings
Sometimes you need a real quantum computer — and when you do, we'll get you there. But if you want your developers iterating daily, learning fast, and building your quantum IP portfolio, simulation belongs at the core of their toolkit.
| Capability | Real QPUs | Quantum Rings |
|---|---|---|
| Run on hardware you already own | ||
| No queue times | ||
| Repeatable results | ||
| Logical qubits | 0–50 | Hundreds |
| Free for non-commercial use | Credits | |
| Incremental cost per run | Per shot | None |
| Fidelity | Low | High |
| Error rates | High | Low |
| Data residency | Out of your control | Stays in your network |
Validating on hardware matters — that's why Open Quantum puts real QPUs a click away. But the day-to-day work of quantum development — iterating on algorithms, training your team, and building IP your company owns — happens fastest in simulation: no queues, no per-shot costs, and your circuits never leave your network.
Works With Your Existing Code
Drop Quantum Rings into the tools and platforms you already use.
Try it
As Easy as One pip install Away
Quantum Rings drops into your existing Qiskit workflow — install the toolkit, swap the backend, and your circuits run at scale on hardware you already own.
pip install quantumrings-toolkit-qiskitfrom qiskit import QuantumCircuit, transpile
from QuantumRingsLib import QuantumRingsProvider
from quantumrings.toolkit.qiskit import QrBackendV2
# Your existing Qiskit circuit — unchanged
qc = QuantumCircuit(64)
qc.h(0)
for i in range(63):
qc.cx(i, i + 1)
qc.measure_all()
# Swap your simulator for Quantum Rings
provider = QuantumRingsProvider(token="<YOUR_TOKEN>", name="<YOUR_ACCOUNT_NAME>")
backend = QrBackendV2(provider, num_qubits=qc.num_qubits)
job = backend.run(transpile(qc, backend), shots=100)
print(job.result().get_counts())Or, do it all in Quantum Rings
Prefer the native API? Same result, no Qiskit required.
pip install QuantumRingsLibfrom QuantumRingsLib import (
QuantumRingsProvider, QuantumRegister,
ClassicalRegister, QuantumCircuit, job_monitor,
)
provider = QuantumRingsProvider(token="<YOUR_TOKEN>", name="<YOUR_ACCOUNT_NAME>")
backend = provider.get_backend("scarlet_quantum_rings")
# Build a 64-qubit GHZ state
q, c = QuantumRegister(64, "q"), ClassicalRegister(64, "c")
qc = QuantumCircuit(q, c)
qc.h(0)
for i in range(qc.num_qubits - 1):
qc.cnot(i, i + 1)
qc.measure_all()
job = backend.run(qc, shots=100)
job_monitor(job)
print(job.result().get_counts())Backends
Pick the Engine That Fits Your Hardware
From any laptop to multi-GPU workstations — one API, three backends.
Scarlet
CPUOur universal engine — runs anywhere, no special hardware. Small circuits run fast at high fidelity, well ahead of statevector simulators — and it scales all the way up to the largest, most complex circuits, even the 2019 quantum supremacy circuits.
Amber
GPU (CUDA)The same universal engine, accelerated by NVIDIA GPUs — up to 40× faster, depending on the circuit.
Serin
HybridA hybrid CPU + GPU engine that offloads to the GPU when it pays off — balancing scale and speed on the hardware you have.
GPU acceleration
Accelerated by NVIDIA
Tap NVIDIA GPUs and CUDA-Q for up to 40× faster runs, depending on the circuit — with support for the NVIDIA GB10 Superchip and CUDA 12.x/13.x. The same circuits, now at GPU speed.
- NVIDIA CUDA-Q integration
- A100 & GB10 Superchip
- Hybrid CPU/GPU pipeline
- Same near-perfect fidelity
Hybrid CPU/GPU pipeline — arXiv:2512.07311
Trusted by researchers
What People Are Saying
“We're excited to see the innovation that will ensue when our researchers leverage this capability at scale.”
“Quantum Rings is perhaps the most advanced simulator on the market today, executing hundreds of qubits on your laptop!”
Published research
Backed by Published Research
Our claims aren’t marketing — they’re published, with methods and numbers anyone can check. We simulate Google’s “quantum supremacy” circuits on accessible hardware, with the fidelity and speedups to prove it.
Need a Real QPU? Open Quantum Has You Covered.
When it's time to run on hardware, take the same code to real QPUs from IonQ, Rigetti, IQM, and AQT — one interface, no contracts, and $50 in free compute credits with every new account.
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