QuEra's 256-qubit

quantum processor

Aquila is QuEra’s first-generation machine. Its core is based on programmable arrays of neutral Rubidium atoms, trapped in vacuum by tightly focused laser beams.

**Large and powerful**With up to 256 qubits and tens of coherent Rabi oscillations, Aquila is uniquely suitable for simulating quantum dynamics at scales that are impractical for classical resources.

**Robust to noise**Operating in the analog quantum processing mode, Aquila performs continuous temporal control over its qubits. This solves one of the key issues for today’s gate-based computers: the compounding of gate errors. Entanglement is generated and manipulated via direct design of Aquila’s atomic natural Hamiltonian.**Flexible programmability**With customer-defined qubit layout and connectivity, Aquila enables unique strategies for algorithm development. Aquila is ready for the easy deployment of applications in quantum simulation, optimization, and machine learning.

****General access to Aquila can be obtained through the Amazon Braket service.

Programming instructions can be generated via the AWS Braket SDK, based on Python.

Need help? Check out some examples here, or visit the Amazon Braket forum.**Amazon Braket availability windows*:**

QuEra’s direct customers and partners enjoy top-tier support as well as premium access to new functionality.

Reach out to us to inquire about our partnership models.

Reach out to us to inquire about our partnership models.

Aquila’s analog mode operation covers a wide family of Hamiltonians within the format

\(\frac{H}{\hbar} = \sum\limits_{i} \frac{\Omega(t)}{2} \left( e^{i \phi(t) } | 0_i \rangle \langle 1_i | + h.c. \right) - \Delta(t)\sum\limits_{i} \hat{n}_i + \sum\limits_{i < j} V_{ij} \hat{n}_i \hat{n}_j\)

\(n_i = |1_i \rangle \langle 1_i |\)

\(V_{ij} = \frac{C_6}{\left|r_i - r_j \right|^6}\)

General parameter ranges can be seen on the table to the right and more information can be found in the getting started example.

Table of user controllable parameters

Programming analog quantum computers is a powerful way to develop applications for large quantum systems efficiently. To best leverage the strengths of this operation mode, make sure to:

Reprogramming qubit positions and controlling their connectivity means that a wide range of problems can be mapped to Aquila’s native Hamiltonian. Don’t forget to leverage this to create different lattices, encode gauge constraints, and explore optimization in a wide range of graph mapping strategies, as done here.

Smooth time evolutions substitute digital gates here. Remember that several protocols benefit from avoiding the errors of compounding gates, such as quantum evolution by Trotterization.

Don’t always rely on classical simulation for benchmark. Aquila’s capacity for quantum dynamical evolution is at the limit of classical.