# NVIDIA Accelerated Quantum Center (NVAQC)

Providing a state-of-the-art facility for turning qubits into useful quantum computers.

Overview

## What is the NVAQC?

The NVIDIA Accelerated Quantum Computing (NVAQC) Research Center is a facility dedicated to shortening the timeline to useful [quantum computing](https://www.nvidia.com/en-us/solutions/quantum-computing.md). The NVAQC integrates partner quantum hardware with state-of-the-art [NVIDIA GB200 NVL72 Grace Blackwell Superchips](https://www.nvidia.com/en-us/data-center/gb200-nvl72.md) via the [NVIDIA DGX™ Quantum](https://www.nvidia.com/en-us/data-center/dgx-quantum.md) architecture. Researchers and developers can orchestrate these quantum-classical systems with the NVIDIA [CUDA-Q™](https://developer.nvidia.com/cuda-q) platform to provide the missing tools to solve pressing challenges such as quantum error correction and hybrid application development. The NVAQC is where qubits become large-scale, accelerated quantum supercomputers capable of exploring useful applications. Watch the video below to learn more about [accelerated quantum supercomputing](https://youtu.be/7rHbdDCdibI).

![YouTube Video](https://img.youtube.com/vi_webp/7rHbdDCdibI/maxresdefault.webp)

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### NVIDIA to Build Accelerated Quantum Computing Research Center

A new center in Boston plans on collaborating with the quantum ecosystem to advance the development of quantum computing architectures and algorithms.

[Read Press Release](https://nvidianews.nvidia.com/news/nvidia-to-build-accelerated-quantum-computing-research-center)

Benefits

## How ‌NVAQC Changes Quantum Computing

Many of the challenges standing between today’s quantum computers and useful devices can only be addressed with AI supercomputing. The NVAQC brings these tools to the quantum computing community.

### Scaling Quantum Hardware

Useful quantum computers will likely be data center-scale devices, requiring integration with conventional AI supercomputers such as the NVAQC to be controlled and operated at scale.

### Correcting Quantum Errors

Quantum error correction is a key tool for large-scale useful quantum computers, but its success rests on challenging computational tasks like decoding. These call for AI and GPU-acceleration techniques, which will be developed at the NVAQC.

### Simulating New QPU Designs

For quantum error correction to work, QPU hardware needs to be highly performant. Rapidly converging on new, more performant qubit designs requires comprehensive and challenging hardware simulations, running on AI supercomputers like the NVAQC.

### Developing Hybrid Algorithms

Useful quantum applications are hybrid, requiring both quantum and classical performant hardware. The NVAQC collocates both hardware modalities allowing researchers to use NVIDIA CUDA-Q to explore truly hybrid applications.

Components

## Powering the NVAQC

The state-of-the-art NVIDIA technologies inside the NVAQC.

### NVIDIA DGX Quantum

* The integrated system for quantum-accelerated computing.
* NVIDIA DGX Quantum runs hybrid algorithms, quantum error correction, calibration, and control at max performance.

[Learn More About DGX Quantum](https://www.nvidia.com/en-us/data-center/dgx-quantum.md)

### NVIDIA GB200 NVL72

* The NVIDIA GB200 NVL2 platform brings the new era of computing to every data center, delivering unparalleled performance for mainstream large language model (LLM) inference, vector database search, and data processing through two [NVIDIA Blackwell](https://www.nvidia.com/en-us/data-center/technologies/blackwell-architecture.md) GPUs and two [NVIDIA Grace™ CPUs](https://www.nvidia.com/en-us/data-center/grace-cpu.md).

[Learn More About GB200 NVL72](https://www.nvidia.com/en-us/data-center/gb200-nvl72.md)

### NVIDIA CUDA-Q

* NVIDIA CUDA-Q is the QPU-agnostic platform for accelerated quantum supercomputing.
* The platform’s hybrid programming model allows computation on GPU, CPU, and QPU resources in tandem from within a single quantum program and the software needed to run useful, large-scale quantum computing applications.

[Learn More About CUDA-Q](https://developer.nvidia.com/cuda-q)

Partners

## NVAQC Partners and Ecosystem

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