Harness the true potential of intelligent compute. NIRVANA brings world-class, continuous-variable quantum AI processing to room-temperature environments.
Topological Polaritons embedded in silica spheres. Operates at 300K with zero cryogenic infrastructure.
7 spheres × 21 comb teeth + 1 edge state. A military-grade continuous-variable architecture.
Spin-wave storage via YIG ferrite crystals. Coherence times measured in rigid seconds.
Fiber-optic daisy-chain linkage. Stack logical units securely without compounding error rates.
QualiumOS compiles PyTorch tensors directly into high-fidelity RF pulses. Bypassing abstraction layers for maximum operational efficiency.
QualiumOS compiles PyTorch tensors directly into high-fidelity RF pulses. By bypassing abstraction layers, it provides unparalleled, bare-metal access to the quantum hardware, ensuring maximum operational efficiency and nanosecond-tier execution.
Initialize Environmentimport torchquantum as tq
class QualiumCircuit(tq.QuantumModule):
def __init__(self):
super().__init__()
self.n_wires = 4
def forward(self, q_device: tq.QuantumDevice):
# Add gates to the circuit grid
# PyTorch Quantum tensor operations will compile here automatically
return tq.measure(q_device, wires=[0, 1, 2, 3])
| Parameter | Legacy Systems | NIRVANA CORE |
|---|---|---|
| Operating Temperature | 0.015K (-273.1°C) | 300K (27°C) |
| Form Factor | Chandelier/Room Size | Desktop/Rack Mount |
| Native Tensor Math | No (Binary Mapping Required) | Yes (Continuous Variable) |
| Cost per Qubit | ~$10,000 | ~$1.00 |
| Coherence Time | Microseconds | Rigid Seconds |
| Cryogenics Required | Yes (Liquid Helium) | None |
| Setup Time | 6-12 Months | 4-8 Hours |
| Power Consumption | 100kW+ | < 800W |
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