Bringing industries into the quantum age with neutral atoms quantum computing.

Explore Our Fullstack Quantum Processors

Generation 1

Currently in production





Generation 2

Currently in research & development.

1,000 QUBITS

Generation 3

Currently in research & development


What differentiates us?

PASQAL’s quantum computers control neutral atoms with optical tweezers, using laser light to manipulate quantum registers with up to a few hundred qubits.


Superior Scalability

Superior Scalability

Our technology enables us to control neutral atoms with optical tweezers and engineer full-stack processors with high connectivity and scalability. We currently operate on 300+ qubits and remain on the path for 1000 qubits.


Analog & Digital

Analog & Digital

PASQAL embraces the dual analog/digital nature of quantum computing, with promise for quantum advantage in the very near-term.


Risk Management

Risk Management

Our quantum computers are available on the cloud, already demonstrating their value in industry-relevant use cases for a wide range of customers.

Our emulators

A cluster of 10 DGX nodes, each equipped with 8 NVIDIA A100 GPUs, allow the emulation of PASQAL’s quantum processors. A key tool to gain flexibility. Up to 100 qubits in 2D and 3D arrays can be emulated to develop industrial applications and to advance scientific discovery.

15 Qubits

Run on laptop

40 Qubits

GPU Cluster

100 Qubits

GPU Cluster, Tensor Networks

Analog Quantum Advantages

PASQAL is taking decisive steps to bring analog quantum advantage to industrial applications.

We are convinced that we can bring quantum advantage to our customers in the very near-term. PASQAL’s QPU can implement both analog and digital quantum processing tasks. The analog mode offers high control of the system and fine-tuning of the different physical parameters. The company is taking decisive steps to bring analog quantum advantage to industrial applications. One very promising direction is solving differential equations, echoing the history of classical computing. The company has also relied on its analog mode to enable novel quantum-enhanced machine learning techniques. And, our focus has been on graph-related problems.

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