Building quantum computers from
neutral-atom arrays

How does it work?

Performing computations with neutral atoms comes down to realizing, controlling, manipulating and measuring neutral-atom qubits. Here, we dive into some details.

The unique characteristics of neutral atoms
Nature's perfect qubits
Quantum error correction
Efficient error correction
High-quality multi-qubit gates
High-quality multi-qubit gates
Small footprint quantum technology
Small footprint
Field-programmable neutral atom quantum arrays
Field programmable atom arrays
Scalable quantum architecture
Highly scalable architecture
High-performance quantum computing architecture
Modular architecture
Analog and digital quantum computation mode
Hybrid operation modes
Quantum advantage
Post-classical compute power

Our qubits are made of neutral atoms

Atoms consist of a nucleus and their electron cloud. At QuEra, we use Rubidium atoms. When the positive and negative charges of an atom balance each other, the atom is said to be neutral, just like most atoms are found in nature. By shining a laser at the atom, we can increase the energy of the atom, and excited it. Each atom has a wide range of potential excited states, each at different energy levels. This offers a great platform for storing and processing quantum information. Any choice of two such levels can be named ‘0’ and ‘1’ to form a qubit.

Two-level energy state for a neutral atom
Trapping rubidium atom with optical tweezers

Controlled by lasers

Using lasers as optical tweezers, we trap individual atoms in their place. The lasers suppresses the atomic movement, effectively cooling atoms down to nearly absolute zero temperature. At these temperatures, the individual discrete energy levels of the atoms can be resolved and manipulated. Some of them leading to huge coherence times exceeding one second.

Nature's perfect qubits
Atoms are nature's perfect qubits, all identical to one another. They are simultaneously capable of storing and processing quantum information, without significant cryogenic requirements. This gives an edge over manufactured qubits that can suffer from imperfections.

Perform Computations by puffing atoms

When atoms are excited to high-energy states, called Rydberg states, their electron clouds are puffed up to relatively enormous scale. Such atoms grow  by more than a thousand times their usual size. In this Rydberg state, different atoms can interact over long distances, enabling quantum information to be transferred between them. This enables entanglement, one of the key ingredients for quantum information manipulation.

The mechanism by which Rydberg atoms interact is called the ‘van der Waals’ interaction, originating from the strong dipole moments of the puffed atoms. This interaction decays with the 6th power of the interatomic distance, meaning that atoms interact very strongly with each other only when they very close. In fact, that interaction can be so strong that it can lead to the so-called "Rydberg blockade" effect, under which no two neighboring atoms can be excited at a given time. Through this mechanism, conditional quantum logic and two-qubit gates can be implemented.

Rydberg interaction in neutral atoms
Quantum error correction
Efficient error correction
Rydberg atoms interact on-demand. When atoms are not excited, they are protected from errors, regardless of the total number of qubits in the system. This significantly increases the computational power of our machines.
Implementing Toffoli gates using digital and analog quantum computing mode

Entangling multiple qubits

Remarkably, the size of Rydberg atoms can include several proximate qubits, enabling all of them to  interact with each other. While most quantum computers can only implement native 1-qubit and 2-qubit gates, the Rydberg blockade mechanism enables the creation of native multi-qubit gates.

Such gates, like the Toffoli gate (see image on the left), play an important role in many quantum algorithms. Encoding these multi-qubit gates natively can substantially reduce the algorithm’s circuit depth, thus also strongly mitigating errors. A good example is the constant-depth implementation of Shor’s algorithm.

High-quality multi-qubit gates
High-quality multi-qubit gates
Long-range Rydberg interactions can be used to reduce the gate-decomposition overhead of multi-qubit gates. This minimizes errors and increases processing speed.

A tiny footprint

All of this happens on a miniature scale: one can pack thousands of laser-trapped atoms in a square millimeter. And with integrated photonic chips, precise control of multiple qubits is achieved by just a few lasers.

Neutral atoms arranged on a grid
Tightly-arranged neutral atom arrays for quantum computing
Small footprint
The atoms and control system for a neutral-atom quantum computer can easily fit in a room. This small footprint makes a neutral atom computers easily deployable in a lab or a data center, without requiring cryogenic cooling.
Interesting arrangements of neutral atom arrays

Flexible configurations

As lasers can move freely through space, neutral atoms can also be arranged in nearly-arbitrary configurations. This allows adjusting and adapting the qubit connectivity to the specific needs of each problem. It also leads to significantly shorter development cycles, as new applications can make use of new configurations without reassembly of the hardware.

Atom shuttling
Field programmable atom arrays
The flexible arrangements of qubits enable reconfigurable layouts. This can be leveraged in algorithm design to limit gate overhead. It leads to significantly shorter development cycles, as new applications requiring different configurations can be implemented without reassembly of the hardware.

Qubit shuttling

With a proper choice of atomic levels for qubit encoding, atoms can even be coherently moved around during a calculation. This is a key advantage of neutral-atom technology. It enables an efficient memory bus service, allowing all-to-all connectivity of the qubits at large scale. This is particularly beneficial in error correction, as it offers new opportunities for choosing gates and error-correcting codes. One example is our first and only realization of Kitaev's paradigmatic toric code with periodic boundary conditions. Furthermore, qubit shuttling enables zoned architectures for memory and processing, further improving the ratio of control lines to number of qubits.

Together, these features make neutral-atom quantum computers the architecture of choice for utility and scalability.

Atom suttling on QuEra's quantum computer
Qubit shuttling
Highly scalable architecture
The small size and efficient control mechanisms allow for dramatic increases in the number of qubits.

Digital and analog quantum operations

Neutral atoms uniquely support different computation modes: digital and analog, each with their own advantages. Users of QuEra's computer will be able to choose the best mode for the particular problem they want to solve.

gate-based quantum circuit

The digital mode

The digital gate-based mode decomposes a complex operation into a few elementary steps (gates) that operate on one or two qubits at a time. The gates move qubits between their two computational states.  Gate sequences change the computational state of the entire system from one state into another. When measured, the final state becomes a bit string,  capturing the outcome of the computation.

Gate-based operation modes provides an elegant recipe to enable universal functionality and programmability, with only a small set of elementary operations.

Analog and digital quantum computing modes
A modular architecture
The core neutral atom processor can be equipped with modules for different functionalities, such as to enable digital quantum gates, error correction, memory and processing zones. This enables rapid hardware development cycles with a flexible roadmaps to accommodate new applications.

The analog quantum mode

At the physical level, digital quantum operations are continuous state transitions expressed by a Hamiltonian: the function that describes the forces that make a physical system change over time. If one can control a Hamiltonian well-enough, the gate-based mode can be bypassed in favor of an analog computation mode. The analog mode is not as universal as the gate-based mode, but when it is possible, it leads us directly to answers without decomposing algorithms into elementary steps, avoiding many of the noise and coherence issues that are common in digital computation modes.

Hamiltonian of an analog quantum computer
Unique analog quantum computing mode
Hybrid operation modes
The ability to work in analog mode, digital mode or the combination of both, allows users to choose the optimal mechanism to reach high-quality solutions to the problems on hand.
The tradeoff between analog and digital computation modes for quantum computers

Scalability vs. programmability

In the digital gate-based mode, errors can be introduced at each step, and accumulate over the course of a computation. In contrast, analog mode does not suffer from accumulation of faulty gates and is therefore much less susceptible to errors, making it very suitable for the current stage of quantum computing maturity.

Combined with simplified control requirements, the analog quantum mode enables efficient manipulation of many more qubits with significantly fewer control signals.

Quantum advantage
Post-classical compute power
Robustness to errors, combined with efficient control mechanisms enabled the assembly of our 256 qubits machine. This machine is powerful enough to enter a nonsimulatable regime for a range of practical problems, surpassing the capabilities of classical supercomputers.