Physicists Build the Largest Qubit Array for Solving Quantum Optimization Problems

An innovative technique for manipulating quantum bits of matter has been demonstrated by physicists from MIT and Harvard University. The technique, which involves using a system of finely-tuned lasers to initially trap and then tune the interactions among 51 individual atoms (i.e. quantum bits), has been described in a paper published in the Nature journal on November 29, 2017.

The outcomes achieved by the team depict one of the biggest quantum bit arrays, or qubit arrays, which could be individually controlled by researchers. In the same issue of the journal Nature, a research group from the University of Maryland has described a system of analogous size developed by using trapped ions as the quantum bits.

In the technique by the MIT-Harvard team, the physicists produced a chain of 51 atoms and programmed them to gundergo a quantum phase transition wherein each and every atom in the chain was excited. The pattern is looks similar to a magnetic state know as antiferromagnetism, where the spin of every other atom or molecule is aligned.

The researchers explains that the 51-atom array is not quite a generic quantum computer, which theoretically has the potential to solve any computational challenge faced by it, but similar to a “quantum simulator,” that is, a quantum bit system that can be made to simulate a particular problem or solve a specific equation quite faster than the most fast classical computer.

For example, the researchers can reconfigure the atomic pattern to simulate and investigate new states of matter and quantum phenomena (e.g. entanglement). The innovative quantum simulator can also be fundamental in solving optimization problems, for instance, the traveling salesman problem where a theoretical salesman has to find out the shortest path to take to visit a mentioned list of cities. Scientists have come across minor variations of this problem in various other research areas, such as moving an automated soldering tip to several soldering points, DNA sequencing, or routing data packets through processing nodes.

This problem is exponentially hard for a classical computer, meaning it could solve this for a certain number of cities, but if I wanted to add more cities, it would get much harder, very quickly, for this kind of problem, you don’t need a quantum computer. A simulator is good enough to simulate the correct system. So we think these optimization algorithms are the most straightforward tasks to achieve.

Vladan Vuletić, Lester Wolfe Professor of Physics, MIT, co-author of this paper.

Harvard professors Mikhail Lukin and Markus Greiner were also collaborators in the study; Sylvain Schwartz, an MIT visiting scientist, is also a co-author of the study.

Separate but interacting

Quantum computers are chiefly theoretical devices with the ability to perform highly complex computations in just a fraction of the time needed for the most powerful classical computer in the world. They achieve this by using qubits, which are data processing units that, in contrast to the binary bits of classical computers, can be in a position of 0 and 1 at the same time. This quantum characteristic of superposition enables a single qubit to perform two individual computation streams at the same time. The addition of more qubits to a system can exponentially accelerate the computations of a computer.

However, major impediments have hindered the achievement of a fully functional quantum computer. One of the impediments is making qubits interact with each other without interacting with the environment around them.

“We know things turn classical very easily when they interact with the environment, so you need [qubits] to be super isolated,” stated Vuletić, a member of the Research Laboratory of Electronics and the MIT-Harvard Center for Ultracold Atoms. “On the other hand, they need to strongly interact with another qubit.”

Certain research teams are constructing quantum systems out of ions (i.e. charged atoms) as qubits. They isolate or trap the ions from the surrounding environment by using electric fields. Upon being isolated, the ions actively interact with one another. However, majority of such interactions are vigorously repelling, similar to magnets of the same polarity, and hence they cannot be easily controlled, specifically in systems that have a high number of ions.

Other teams have been conducting experiments by using superconducting qubits, or artificial atoms engineered to act in a quantum manner. However, according to Vuletić, engineered qubits have many drawbacks in contrast to the ones made using actual atoms.

“By definition, every atom is the same as every other atom of the same species,” stated Vuletić. “But when you build them by hand, then you have fabrication influences, such as slightly different transition frequencies, couplings, et cetera.”

Setting the trap

Vuletić and his team formulated a third strategy to construct a quantum system by using neutral atoms (or atoms with no electrical charge) as qubits. In contrast to ions, neutral atoms never repel one another, and they include intrinsically identical characteristics when compared to engineered superconducting qubits.

In an earlier study, the team came up with a technique to isolate individual atoms by using a laser beam to initially cool a cloud of rubidium atoms to nearly absolute zero temperatures, making their motion slow to almost stationary. Subsequently, they used another laser, which was split into over 100 beams, to isolate and position individual atoms in place. They could image the cloud to observe the laser beams that have trapped an atom, and could then switch off specific beams to get rid of the traps that did not have an atom. Then, they rearranged all the traps that included atoms to form a defect-free, ordered qubit array.

By using this approach, the scientists could form a quantum chain of 51 atoms, all isolated at their ground state, that is, lowest energy level.

In the new paper, the researchers have reported that they have went one step closer to regulating the interactions of the 51 trapped atoms, a significant step in controlling individual qubits. In order to achieve this, they turned off the laser frequencies that actually trapped the atoms for some time, thus enabling the quantum system to evolve naturally.

Subsequently, the team irradiated a third laser beam on the evolving quantum system to attempt and excite the atoms to go into a Rydberg state, or a state in which one electron in an atom is excited to an extremely higher energy level in contrast to the remaining electrons of the atom. Lastly, they turned on the atom-isolating laser beams to investigate the final states of the individual atoms.

“If all the atoms start in the ground state, it turns out when we try to put all the atoms in this excited state, the state that emerges is one where every second atom is excited,” stated Vuletić. “So the atoms make a quantum phase transition to something similar to an antiferromagnet.”

The transition occurs only in alternate atoms because atoms in Rydberg states strongly interact with one another, and even higher energy is needed to excite two neighboring atoms to Rydberg states than the energy from the laser.

According to Vuletić, the scientists can alter the interactions between atoms by modifying not only the arrangement of trapped atoms but also the color or frequency of the atom-exciting laser beam. This enables easy expansion of the system.

“We think we can scale it up to a few hundred,” stated Vuletić. “If you want to use this system as a quantum computer, it becomes interesting on the order of 100 atoms, depending on what system you’re trying to simulate.”

At present, the team is hoping to investigate the use of the 51-atom system as a quantum simulator, particularly on path-planning optimization problems that can be resolved by adopting adiabatic quantum computing, a kind of quantum computing first put forward by Edward Farhi, the Cecil and Ida Green Professor of Physics at MIT.

According to adiabatic quantum computing, a quantum system’s ground state elucidates the resolution to the problem of interest. If that system can be modified to generate the problem itself, the system’s end state can confirm the solution.

“You can start by preparing the system in a simple and known state of lowest energy, for instance all atoms in their ground states, then slowly deform it to represent the problem you want to solve, for instance, the traveling salesman problem,” stated Vuletić. “It’s a slow change of some parameters in the system, which is exactly what we do in this experiment. So our system is geared toward these adiabatic quantum computing problems.”

The National Science Foundation, the Army Research Office, and the Air Force Office of Scientific Research partially supported the study.