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In the quest for quantum supremacy, the race to develop the best quantum bit (qubit) technology is heating up. Quantum computers, which leverage the principles of quantum mechanics, promise to solve problems that are currently intractable for classical computers. However, achieving practical quantum computing and developing quantum sensors requires robust, reliable, and scalable qubit technologies. In this article, we delve into the leading qubit technologies and explore the fierce competition driving innovation in this field.
Understanding Qubits
Quantum technology (QT) applies quantum mechanical properties such as quantum entanglement, quantum superposition, and No-cloning theorem to quantum systems such as atoms, ions, electrons, photons, or molecules. Quantum entanglement is a phenomenon where entangled particles can stay connected in the sense that the actions performed on one of the particles affects the other no matter what’s the distance between them. No-cloning theorem tells us that quantum information (qubit) cannot be copied.
Quantum bit is the basic unit of quantum information. Whereas in a classical system, a bit is either in one state or the another. However, quantum qubits can exist in large number of states simultaneously, property called Superposition. Unlike classical bits, which can only be in one state at a time (either 0 or 1), qubits can exist in a superposition of states, enabling quantum computers to perform certain calculations exponentially faster than classical computers. Qubits also exhibit entanglement, a phenomenon where the state of one qubit is directly related to the state of another, regardless of distance. These properties enable quantum computers to process information in ways that classical computers cannot.
Quantum technologies have the potential to spur revolutions in computing, sensing, cryptography and beyond. By taking advantage of those properties, quantum computers can process information in new ways, potentially performing calculations far beyond the reach of even the fastest of today’s supercomputers. They can simultaneously consider different possible solutions to a problem and quickly converge on the correct solution without checking each possibility individually. This dramatically speed up certain calculations, such as number factoring.
The Nature of Qubits
Qubits represent atoms, ions, photons, or electrons and their respective control devices, which work together to act as both computer memory and processor.
Qubits can be formed from any system with two possible quantum mechanical states. Examples include:
- Electron spins: The spin of an electron can be in an “up” or “down” state.
- Photon polarization: A photon can have vertical or horizontal polarization.
- Superconducting circuits: Quantum states are represented by oscillations in superconducting loops.
- Ions in traps: Single ions held in place by electric and magnetic fields.
Calculations using these noisy qubits can introduce errors and make long computations impossible. However, these computers still can demonstrate the advantages of quantum computing and various algorithms are being developed in disciplines such as machine learning, quantum chemistry and optimization.
Requirements for Qubits in Quantum Computing
Qubits represent atoms, ions, photons or electrons and their respective control devices that are working together to act as computer memory and a processor. Examples include: the spin of the electron in which the two levels can be taken as spin up and spin down; or the polarization of a single photon in which the two states can be taken to be the vertical polarization and the horizontal polarization. In a classical system, a bit would have to be in one state or the other.
Any system with two possible quantum mechanical states — such as the oscillations in a superconducting loop or energy levels of an ion — could form a qubit, but all hardware types have pros and cons, and each faces substantial hurdles to forming a full-blown quantum computer. A machine capable of living up to the original promise of quantum computing by, for example, cracking conventional encryption, would require millions of individually controllable qubits. But size is not the only issue: the quality of the qubits and how well they connect to each other are just as important.
The power of quantum computers depends on the number of qubits and their quality measured by coherence, and gate fidelity. Qubit is very fragile, can be disrupted by things like tiny changes in temperature or very slight vibrations. Coherence measures the time during which quantum information is preserved. The gate fidelity uses distance from ideal gate to decide how noisy a quantum gate is.
One of the major differences between a classical computer and a quantum computer is in how it handles small unwanted variations, or noise, in the system. Since a classical bit is either one or zero, even if the value is slightly off (some noise in the system) it is easy for the operations on that signal to remove that noise. In fact, today’s classical gates, which operate on bits and are used to create computers, have very large noise margins—they can reject large variations in their inputs and still produce clean, noise-free outputs. Because a qubit can be any combination of one and zero, qubits and quantum gates cannot readily reject small errors (noise) that occur in physical circuits. As a result, small errors in creating the desired quantum operations, or any stray signals that couple into the physical system, can eventually lead to wrong outputs appearing in the computation. Thus, one of the most important design parameters for systems that operate on physical qubits is their error rate.
1. Scalability
A scalable physical system containing a collection of well-characterized qubits is essential. To realize the full potential of quantum computing, machines need to manage millions of qubits. This scalability must come without significant degradation in performance or increased error rates. Applying quantum computing to practical problems hinges on the ability to scale to and control thousands – if not millions – of qubits at the same time with high levels of fidelity. However, current quantum systems designs are limited by overall system size, qubit fidelity and especially the complexity of control electronics required to manage the quantum at large scale.
2. Initialization
The ability to initialize the qubits to a simple fiducial state is crucial. This means setting qubits to a known starting state before computations begin, ensuring consistency and reliability in quantum operations.
3. Decoherence Time
Qubits need to maintain coherence for long periods. Quantum coherence refers to the state of qubits remaining in superposition. Longer coherence times are vital as they directly influence the performance and fidelity of quantum operations. Decoherence, caused by interactions with the external environment, remains a significant hurdle.
The qubits need to stay coherent for long periods of time. This is when their state is still in Superposition – i.e. hasn’t collapsed to zero or one which is known as decoherence. Quantum coherence is at the heart of quantum information technology. The latter can only be realised as long as quantum coherence is preserved. In fact, as quantum applications increase in complexity, coherence time needs to be extended. In a similar manner, longer coherence times reveal higher performance and higher quantum operation fidelity, which is extremely important especially for quantum computing.
4. Quantum Gates
In quantum computing and specifically the quantum circuit model of computation, a quantum logic gate (or simply quantum gate) is a basic quantum circuit operating on a small number of qubits. They are the building blocks of quantum circuits, like classical logic gates are for conventional digital circuits. Quantum gates can leverage two key aspects of quantum mechanics that are entirely out of reach for classical gates: superposition and entanglement. It needs to achieves quick gate operations:
A “universal” set of quantum gates is required for performing quantum computations. This includes single-qubit rotations and multi-qubit gates like CNOT or C-Phase. High gate fidelity, where operations preserve quantum information accurately, is essential to mitigate the effects of noise and errors.
Overcoming Challenges in Quantum Computing
We are now in era of Noisy intermediate-scale quantum (NISQ) in which quantum computers are composed of hundreds of noisy qubits that are not error-corrected. They Physical qubits are realized using superconducting Josephson junction qubits and the trapped-ion qubits. Other promising Qubits are Semiconductor based qubits; Topological qubits; and Photonic qubits.
For future fault-tolerant quantum computers Researchers have devised error-correction schemes such as surface code, that store data redundantly with information spread over tens of thousands of entangled physical qubits. These combined bits are collectively known as a logical qubit or perfect qubit. Previous research has found that a quantum computer with 300 perfect qubits could perform more calculations in an instant than there are atoms in the universe.
1. Error Rates and Quantum Error Correction (QEC)
Quantum operations are highly sensitive to noise, which can lead to errors in computation. Classical bits can reject noise, but qubits are more susceptible to errors due to their quantum nature. Quantum error correction techniques are being developed to emulate a noise-free, fully error-corrected quantum computer.
2. Gate Fidelity and Connectivity
High gate fidelity and strong connectivity between qubits are necessary. Each added gate operation increases the potential for error accumulation, necessitating precise control over qubit interactions. Achieving this requires advanced engineering and error correction methodologies.
3. System Complexity and Control Electronics
Current quantum systems are limited by the complexity of control electronics and the need for maintaining low error rates across many qubits. Effective scaling of quantum computers involves integrating sophisticated technologies that can handle large qubit arrays with minimal noise.
Leading Qubit Technologies
Some of the possible Qubits and implementations are Neutral atoms, Trapped ions, Colour centres (e.g., NV-centers in diamond), Electron spins (e.g,. quantum dots), Superconducting qubits (charge, phase, flux), NMR, Optical qubits and Topological qubits among others.
There have been two leading approaches for building general purpose Quantum computer. One approach, adopted by Google, IBM, Rigetti and Quantum Circuits involves encoding quantum states as oscillating currents in superconducting loops. The other, pursued by IonQ and several major academic labs, is to encode qubits in single ions held by electric and magnetic fields in vacuum traps.
Neutral atoms
Atoms have many energy levels that have been studied extensively over the past century, and some of these energy levels are extremely stable. Indeed, with accuracies better than one part in 10−15, atomic clocks provide the best available time and frequency standards.
The qubits encoded in the atomic energy levels can be initialized by optical pumping and laser cooling, manipulated with electromagnetic radiation, and then measured via laser-induced fluorescence. In short, atoms provide clean, well-defined qubits.
Neutral atoms make attractive qubit candidates also because of their weak interaction with the environment, leading to long coherence times They can be cooled down to nK temperatures and trapped in very large numbers (millions) in microscopic arrays created by laser beams (called optical lattices). The trapping and manipulation of atoms can be done with high precision. While one-qubit gates can be implemented with very high fidelity, realizing twoqubit gates or many-qubit entangled states is challenging because the atoms interact
very weakly with each other
Advantages:
• Production of large quantum registers
• Massive parallelism in gate operations
• Long coherence times (>20s)
Difficulties:
• Gates typically slower than other implementations (~ms for collisional gates) (Rydberg gates can be somewhat faster)
• Individual addressing (but recently achieved)
What: Neutral atoms are a similar approach to Ion Traps but instead of using ionized atoms and exploiting their charge to hold the qubits in place, neutral atoms and laser tweezers are used.
Who: Atom Computing; PASQAL; QuEra.
Pros: Neutral atoms benefit from the same long coherence times as ions (used in Ion Trap quantum computers). Its unique feature compared to Ion Traps is its potential for building multidimensional arrays.
Cons: Scaling up a neutral atom system faces the issues that arise when scaling a trapped ion computer. This approach continues to be highly nascent.
Molecules
A UCLA-led interdisciplinary research team including collaborators at Harvard University has now developed a fundamentally new strategy for building these computers. While the current state of the art employs circuits, semiconductors and other tools of electrical engineering, the team has produced a game plan based in chemists’ ability to custom-design atomic building blocks that control the properties of larger molecular structures when they’re put together.
The findings, published in Nature Chemistry in July 2022, could ultimately lead to a leap in quantum processing power. “The idea is, instead of building a quantum computer, to let chemistry build it for us,” said Eric Hudson, UCLA’s David S. Saxon Presidential Professor of Physics and corresponding author of the study. “All of us are still learning the rules for this type of quantum technology, so this work is very sci-fi right now.
The scientists developed small molecules that include calcium and oxygen atoms and act as qubits. These calcium-oxygen structures form what chemists call a functional group, meaning that it can be plugged into almost any other molecule while also conferring its own properties to that molecule.
The team showed that their functional groups maintained their desired structure even when attached to much larger molecules. Their qubits can also stand up to laser cooling, a key requirement for quantum computing.
“If we can bond a quantum functional group to a surface or some long molecule, we might be able to control more qubits,” Hudson said. “It should also be cheaper to scale up, because an atom is one of the cheapest things in the universe. You can make as many as you want.”
In addition to its potential for next-generation computing, the quantum functional group could be a boon for basic discovery in chemistry and the life sciences, for instance by helping scientists uncover more about the structure and function of various molecules and chemicals in the human body.
“Qubits can also be exquisitely sensitive tools for measurement,” said study co-author Justin Caram, a UCLA assistant professor of chemistry and biochemistry. “If we could protect them so they can survive in complex environments such as biological systems, we would be armed with so much new information about our world.”
Hudson said that the development of a chemically based quantum computer could realistically take decades and is not certain to succeed. Future steps include anchoring qubits to larger molecules, coaxing tethered qubits to interact as processors without unwanted signaling, and entangling them so that they work as a system.
Superconducting circuits
Superconducting circuits are typically µm-scale circuits operated at mK temperatures. Although macroscopic, they can still exhibit quantum behavior, which can be harnessed for QC . Superconducting circuits are RLC circuits that also include nonlinear elements, called Josephson junctions. Thanks to superconductivity, the resistance vanishes (R = 0), eliminating the most serious source of dissipation and noise. Now, the LC circuit is a harmonic oscillator. The problem with harmonic oscillators is that they have an infinite number of equally-spaced energy levels and therefore it is not possible to target only the lowest two energy levels. By introducing nonlinearity through the Josephson junction, the energy-level separation becomes nonuniform, and the lowest two levels can be used to encode the qubit.
This qubit implementation is the most common, and is the main focus of IBM and Google’s universal quantum computers. Others are Rigetti; Alibaba; Intel; Quantum Circuits; Oxford Quantum Circuits.
Quantum information can be encoded in different ways: in the number of superconducting electrons on a small island (charge qubit), in the direction of a current around a loop (flux qubit), or in oscillatory states of the circuit (phase qubit). These qubits can be controlled by microwaves, voltages, magnetic fields, and currents as well as measured with high accuracy using integrated on-chip instruments. Superconducting qubits have coherence times that can reach tens of µs , the coupling between qubits can be made strong and can be turned on and off electronically.
Pros: Superconducting qubits have fast gate times (faster operation time), meaning similar computations can be performed much more quickly than on other qubits (e.g. Ion Trap). This is important since useful quantum computations will likely have millions of logical gates (operations). Additionally, the technology behind superconducting qubits can take advantage of existing methods and processes (such as printable circuits) that we have already spent decades improving. As a result it is easier to envisage a scalable superconducting quantum computer than with some other existing methods.
Cons: Superconducting qubits have fast decoherence times, meaning their ‘memory’ is very short lived and we need more error correcting qubits to compensate. Since superconducting qubits can normally only interact with the handful of qubits next to them on the device, we need extra operations to perform most algorithms. They also must be kept very cold (below 100mK, or 0.1 degrees above absolute zero) which can be expensive and inconvenient. Finally, each superconducting qubit is slightly different and must be calibrated which could cause problems on larger systems.
Trapped Ion Qubits
While neutral atoms interact weakly among themselves, ions, being charged, interact rather strongly via Coulomb repulsion. This facilitates the implementation of twoqubits gates without compromising the long coherence times. Also thanks to their charge, the motion and position of the ions can be well controlled. Ions can be trapped by electrical (or magnetic) fields, laser-cooled and manipulated with high precision. Entangled (Greenberger-Horne-Zeilinger (GHZ) and W) states of up to 14 qubits have been realized .
What: Ion Trap quantum computers work by trapping ions (charged atoms) using electric fields and holding them in place, the outermost electron orbiting the nucleus can then be put in different states and used as a qubit.
Who: IonQ; Alpine Quantum Technologies; Honeywell. But a separate approach, using ions trapped in electric fields, is gaining traction in the quest to make a commercial quantum computer. Honeywell launched its first quantum computer using trapped ions as the basis of its quantum bits or ‘qubits’, which it had been working on quietly for more than a decade. Honeywell, headquartered in Charlotte, North Carolina, is the first established company to take this route. In October, seven months after the launch, the firm unveiled an upgraded machine; it already has plans to scale this up.
Pros: A big feature of Ion Trap computers is their stability; the qubits have much longer “coherence times” than those used in Superconducting quantum computers. While an Ion Trap computer can operate at room temperature, to get the best performance the ions need to be cooled, but not to the extent a Superconducting quantum computer requires. The connections between Ion Trap qubits can be reconfigured meaning each qubit can interact with each other qubit in the computer, avoiding some of the computational overhead found with superconducting chips.
Cons: Ion trap computers are generally significantly slower than their superconducting counterparts. While they do not need to be kept as cold, the ions do need to be in a high vacuum. The technology involved in creating ion traps is not as mature as with superconducting qubits, we will need to see large improvements in the area before we can imagine a scalable system. Building a Ion Trap quantum computer requires integration of technologies from a wide range of domains, including vacuum, laser, and optical systems, radio frequency and microwave technology, and coherent electronic controllers.
Photonic Qubits
Photonic qubits use light particles (photons) to encode and manipulate quantum information. Photons are excellent carriers of quantum information over long distances, making them ideal for quantum communication and certain types of quantum computing.
Advantages: Photons are less susceptible to decoherence and can operate at room temperature. They are suitable for quantum networks and secure communication.
Photons can also make good qubits and they can carry quantum information over long distances hardly being affected by noise or decoherence. The qubit states can be encoded, for example, in the polarization of a single photon, and one-qubit gates can be easily realized with optical elements.
Challenges: Creating reliable photon sources and detectors is challenging, and entangling multiple photonic qubits requires complex optical setups.
Unfortunately optical QC has a serious drawback: the difficulty in implementing two-qubit gates. Realizing the nonlinearity required for entangling two qubits is challenging, so alternatives such as the teleportation of nondeterministic quantum gates have been investigated. While this approach is still impractical due to the large amount of required resources, another solution may be found in measurement-based QC.
In 2014, Pfister’s group succeeded in generating more than 3,000 quantum modes in a bulk optical system. However, using this many quantum modes requires a large footprint to contain the thousands of mirrors, lenses and other components that would be needed to run an algorithm and perform other operations.
What: Photonic qubits are single particles of light (photons) operating on silicon chips pathways.
Who: PsiQuantum; Xanadu.
Pros: The main advantage marketed by industry players is that this implementation does not require extreme cooling, and thus allows for more energy-efficient computation. In addition, given the use of silicon chips, the approach is seen as highly scalable (as it can use existing semiconductor industry infrastructure) rather than having to develop new atomic-scale fabrication techniques.
Cons: The technology is still nascent and key areas such as qubit connectivity are to be demonstrated.
A research team led by Xu Yi, assistant professor of electrical and computer engineering at the University of Virginia School of Engineering and Applied Science, has carved a niche in the physics and applications of photonic devices, which detect and shape light for a wide range of uses including communications and computing. His research group has created a scalable quantum computing platform, which drastically reduces the number of devices needed to achieve quantum speed, on a photonic chip the size of a penny. Through multiplexing, Yi’s team verified the generation of 40 qumodes from a single microresonator on a chip, proving that multiplexing of quantum modes can work in integrated photonic platforms. This is just the number they are able to measure.
Topological qubit
Topological qubits are based on the principles of topological quantum computing, which aims to use quasiparticles known as anyons to encode and process quantum information. Microsoft is a prominent player in this area, focusing on topological qubits for their potential fault-tolerant properties.
Microsoft’s approach to building a quantum computer is based on a type of qubit – or unit of quantum information – called a topological qubit. These operate on a different principle to the other qubits The Microsoft team believes that topological qubits are better able to withstand challenges such as heat or electrical noise, allowing them to remain in a quantum state longer. That, in turn, makes them much more practical and effective. “A topological design is less impacted by changes in its environment,” Holmdahl said.
Advantages: Topological qubits are expected to be inherently protected from certain types of errors, making them more robust and scalable.
Topological quantum computing seeks to implement a more resilient qubit by utilizing non-Abelian forms of matter to store quantum information. Non-Abelian forms of matter are quasiparticles, like Majorana Fermions and Anyons (non-Abelian quasiparticles who are neither bosons or fermions). The most promising topological quantum computing developments derives from a non-Abelian braiding of chiral Majorana Fermions by Quantum Dots. The type of anyon needed to create a universal quantum computer have not been experimentally confirmed yet (but we have some tentative signs). For now, this model of quantum computation is purely theoretical.
Pros: Topological qubits are protected from noise due to their values existing at two distinct points, making our quantum computer more robust against outside interference. This increased stability will help the quantum computer scale to complete longer, more complex computations, bringing the solutions we need within reach. Topological qubits should demonstrate high coherence times and much higher fidelities (lower errors) than other implementations.
Cons: Theoretical
Silicon
What: Artificial atoms made by adding an electron to a small piece of silicon. Microwaves are used to control the electrons state.
Who: Intel; Silicon Quantum Computing.
Pros: If successful, this approach should allow for longer coherence times than the superconducting approach. Working with silicon builds on decades of research from the existing semiconductor industry.
Cons: Unlike Ion Traps, the silicon approach requires cooling. The technology is still highly nascent.
Spins in solids
Coherent control and measurement of single spins in solids is now possible, and this allows using electron spins in semiconductor quantum dots, or electron spins together with nuclear spins in nitrogen-vacancy (NV) color centers in diamond for QC purposes.
Quantum dots are nanoscale structures in which electrons are trapped in all three dimensions. They can be fabricated in several ways, for example, by growth or with electrode gates in a two-dimensional electron-gas. The material of choice is usually GaAs. On the other hand, NV centers are point defects in the diamond lattice, consisting of a nearest-neighbor pair made of a nitrogen atom, substituting a carbon atom, and a lattice vacancy. Although in its early stages, quantum computing with electronic and nuclear spins in an array of phosphorus donor atoms embedded in a pure silicon lattice (P:Si) has recently achieved very encouraging results.
Solid state qubits such as quantum dots are attractive because, like superconducting circuits, they could be designed to have certain characteristics and assembled in large arrays. Furthermore, they require temperatures of up to a few K (NV centers in diamond could operate even at room temperature). The manipulation and readout can be done both electrically and optically.
Nowadays, Nuclear Magnetic Resonance (NMR) techniques are extensively used in the context of nuclear spins in semiconductors. NMR techniques have been used for the control of nuclear spins in molecules , which proved very successful for realizing QC with such nuclear spin qubits
Silicon Spin Qubits
Silicon spin qubits use the spin of electrons or nuclei in silicon to encode quantum information. This approach leverages the extensive knowledge and infrastructure of the semiconductor industry. Companies like Intel are exploring silicon spin qubits as a scalable solution.
Advantages: Silicon spin qubits can be integrated into existing semiconductor manufacturing processes, potentially allowing for large-scale production.
Challenges: Achieving long coherence times and high-fidelity operations in silicon spin qubits is technically challenging, requiring precise control over the quantum states.
Electrons as Qubits
A research team led by the U.S. Department of Energy’s Argonne National Laboratory, in collaboration with Associate Professor Wei Guo from FAMU-FSU College of Engineering, has developed a promising new qubit platform that could significantly advance future quantum computers. Their findings were published in Nature.
Development of the Electron-Based Qubit
The researchers chose a single electron as their qubit, leveraging its simplicity and potential for high coherence times. The qubit was created by freezing neon gas into a solid at very low temperatures, then spraying electrons onto this solid surface and trapping a single electron. Neon, being one of the six inert elements, provides a stable and non-reactive environment for the electron.
Advantages of Solid Neon
- Minimizing Defects:
- Defects in qubit systems can drastically reduce coherence times. The team mitigated this by trapping the electron on an ultrapure solid neon surface in a vacuum, minimizing the potential for defects that could disrupt the electron’s state.
- Stable Medium:
- Unlike previous approaches using liquid helium, which had minimal defects but suffered from surface vibrations, solid neon offers a stable environment that doesn’t vibrate, thus preserving the electron’s state more effectively.
Technical Implementation
- Superconducting Resonator:
- The team used a chip-scale superconducting resonator, akin to a miniature microwave oven, to manipulate the trapped electrons. This setup allowed them to read and store information from the qubit, making it practical for quantum computing applications.
- Microwave Photons:
- Real-time qubit operations were performed using microwave photons on the trapped electron. These operations were critical in characterizing the quantum properties of the qubit.
Results and Implications
- Robust Environment:
- Tests demonstrated that solid neon provided a robust environment for the electron, with very low electric noise to disturb it. This stability is crucial for maintaining the qubit’s coherence.
- Competitive Coherence Times:
- The electron qubit attained coherence times that are competitive with other state-of-the-art qubits, marking a significant achievement in the field.
- Simplicity and Cost-Effectiveness:
- The simplicity of this qubit platform suggests that it could be manufactured easily and at a low cost, which is advantageous for scaling up quantum computing technologies.
The creation of a new qubit platform using a single electron on a solid neon surface marks a significant advancement in quantum computing research. By choosing an inert and stable medium like solid neon, the team has addressed key challenges related to coherence times and qubit stability. The use of a chip-scale superconducting resonator further enhances the practicality of this platform, making it a promising candidate for future quantum computers.
New Techniques for Making Qubits out of Erbium
Introduction
Scientists are developing new methods to create stable and easily manipulated qubits, the building blocks of quantum technology. Erbium, a rare-earth metal, has been identified as an effective qubit. Two research groups—one from the quantum startup memQ and the other from Argonne National Laboratory—have made significant strides in this area using different host materials for erbium. Their work highlights the importance of materials science in quantum computing and communication.
memQ’s Laser Activation Technique
memQ has developed a novel technique to control multi-qubit devices by selectively activating erbium qubits with a laser. Erbium atoms are scattered throughout a film of titanium dioxide (TiO2). By firing a laser at specific areas, the crystal structure of TiO2 changes, allowing only certain erbium atoms to be used as qubits. This method leverages TiO2’s property of having two possible crystal configurations, enabling targeted erbium atoms to communicate at the same frequency.
- Advantages:
- Precision Control: Allows selection of specific erbium atoms for qubit use.
- Effective Communication: Ensures selected erbium atoms communicate at the same frequency.
- Significance: This advancement in solid-state technology addresses the challenge of engineering multi-qubit devices by providing precise control over qubit placement.
Argonne’s Approach to Erbium Qubit Coherence
Argonne National Laboratory focused on extending the coherence time of erbium qubits, a crucial measure of their effectiveness. Erbium qubits retain quantum information using their electron spin. However, interactions with nuclear spins in the host material can cause decoherence. To mitigate this, Argonne researcher Jiefei Zhang chose cerium dioxide (CeO2) as the host material, which has the lowest possible nuclear spin and a highly symmetric crystal structure.
- Advantages:
- Stability: CeO2’s symmetry provides a stable environment for erbium qubits.
- Longer Coherence Times: Demonstrated longer coherence times compared to other materials.
- Pros and Cons: While CeO2 offers stability and longer coherence times, the laser activation technique used by memQ is not feasible with this highly symmetric crystal structure.
Both techniques—memQ’s selective activation of erbium qubits and Argonne’s use of CeO2 for extended coherence—illustrate the diverse approaches in advancing quantum technology. The choice of host material and method of qubit manipulation are critical factors that determine the performance and applicability of quantum devices. These innovations represent significant steps toward realizing practical and scalable quantum computers.
Emerging and Hybrid Approaches
Innovative approaches, including hybrid systems combining different qubit types, offer exciting prospects. For example, interfacing neutral atoms with superconducting circuits or using topological qubits to enhance stability and coherence. These hybrid systems aim to leverage the strengths of each qubit type to overcome individual limitations.
Hybrid quantum systems, which combine the strengths of both natural and artificial atoms, offer promising avenues for advancing quantum computing. By leveraging the complementary advantages of these components, researchers aim to create more robust, scalable, and versatile quantum computers.
Key Concepts and Advantages
- Natural Atoms as Quantum Memories:
- Long Decoherence Times: Natural atoms, such as trapped ions or neutral atoms, possess inherently long coherence times, making them excellent candidates for quantum memory storage. These long decoherence times are crucial for maintaining quantum information over extended periods.
- High Fidelity: Natural atoms can achieve high-fidelity quantum operations, essential for reliable quantum memory and error correction protocols.
- Artificial Atoms as Quantum Processors:
- Tunable Properties: Artificial atoms, such as superconducting qubits, can be precisely engineered and tuned, allowing for flexible control and fast quantum operations. This tunability makes them ideal for quantum processing units (QPUs).
- Rapid Gate Speeds: Superconducting qubits and other artificial atoms can perform quantum gate operations at much faster speeds compared to natural atoms, enhancing computational efficiency.
- Interfacing Natural and Artificial Atoms:
- Cavity Quantum Electrodynamics (CQED): Both natural and artificial atoms can be coupled with photons in optical or microwave cavities. These cavities facilitate strong interactions between qubits and photons, serving as efficient interfaces for information transfer and processing.
- Hybrid Coupling: Recent research has explored the direct interfacing of neutral atoms and ions with superconducting circuits, potentially combining the benefits of both systems in a single hybrid device.
Practical Implementations
- Quantum Memories with Natural Atoms:
- Natural atoms can be employed as reliable quantum memories due to their long coherence times. For instance, trapped ions can store quantum information for extended durations, allowing for complex quantum computations and communication protocols.
- Quantum Processors with Artificial Atoms:
- Artificial atoms, particularly superconducting qubits, are used for fast quantum processing. These qubits can perform numerous quantum operations quickly, making them suitable for executing complex quantum algorithms.
- Photonic Interfacing:
- Cavity Interfaces: Cavities can couple qubits with photons, enabling quantum information to be transferred between different types of qubits and facilitating long-distance quantum communication. This coupling must occur on timescales shorter than the decoherence time to ensure efficient and reliable information transfer.
- Hybrid Systems:
- The first functional quantum computer might be a hybrid system that integrates natural atoms, artificial atoms, and photons. Such a system would capitalize on the strengths of each component, using natural atoms for memory, artificial atoms for processing, and photons for communication.
Hybrid quantum systems represent a promising frontier in quantum computing. By combining the stability and long coherence times of natural atoms with the tunability and fast operations of artificial atoms, researchers aim to develop more powerful and scalable quantum computers. The integration of these elements through advanced interfacing techniques, such as cavity quantum electrodynamics, is expected to pave the way for the first functional hybrid quantum computers, potentially revolutionizing quantum technology and its applications.
The Race for Quantum Supremacy
The competition to develop the best qubit technology is driving rapid advancements in quantum computing. Each qubit technology has its own set of advantages and challenges, and the optimal choice may depend on the specific application. For example, superconducting qubits are well-suited for general-purpose quantum computing, while photonic qubits are ideal for quantum communication.
Researchers and companies worldwide are investing heavily in quantum technologies, forming collaborations, and securing funding to accelerate progress. Governments are also recognizing the strategic importance of quantum computing and are supporting initiatives to foster innovation in this field.
Quantum Sensors: A Parallel Race
In addition to quantum computing, the race for qubit technology extends to quantum sensors. Quantum sensors leverage the sensitivity of qubits to measure physical quantities with unprecedented precision. Applications range from medical imaging and navigation to fundamental physics experiments.
Quantum sensors using different qubit technologies, such as NV centers in diamond (a type of defect in diamond crystals) and atomic vapor cells, are being developed to achieve superior sensitivity and accuracy compared to classical sensors.
Conclusion
The race to develop the best qubit technology is a critical aspect of the broader quest for quantum supremacy. Superconducting qubits, trapped ion qubits, photonic qubits, topological qubits, and silicon spin qubits each offer unique pathways toward building practical quantum computers and advanced quantum sensors. As research and development continue to advance, the realization of scalable and robust quantum technologies draws closer, promising to revolutionize computing, communication, and sensing in the coming years.
Silicon carbide qubit coherence time for a record five seconds, reported in Feb 2022
A team of researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Chicago were able to read out their qubit on demand and then keep the quantum state intact for over five seconds — a new record for this class of devices. Additionally, the researchers’ qubits are made from an easy-to-use material called silicon carbide, which is widely found in lightbulbs, electric vehicles and high-voltage electronics.
“This essentially brings silicon carbide to the forefront as a quantum communication platform,” said University of Chicago graduate student Elena Glen, co-first author on the paper. “This is exciting because it’s easy to scale up, since we already know how to make useful devices with this material.”
The researchers grew highly purified samples of silicon carbide that reduced the background noise that tends to interfere with their qubit functioning. Then, by applying a series of microwave pulses to the qubit, they extended the amount of time that their qubits preserved their quantum information, a concept referred to as “coherence.”
“These pulses decouple the qubit from noise sources and errors by rapidly flipping the quantum state,” said Chris Anderson of the University of Chicago, co-first author on the paper. “Each pulse is like hitting the undo button on our qubit, erasing any error that may have happened between pulses.”
The researchers think that even longer coherences should be possible. Extending coherence time has significant ramifications, such as how complex an operation a future quantum computer can handle or how small a signal a quantum sensor can detect.
“For example, this new record time means we can perform over 100 million quantum operations before our state gets scrambled,” Anderson said.
Every computer needs a way to read information encoded into its bits. For semiconductor qubits, like the ones measured by the team, the typical readout method is to address the qubits with lasers and measure the light emitted back. This procedure is challenging, however, because it requires detecting single particles of light called photons very efficiently.
Instead, the researchers use carefully designed laser pulses to add a single electron to their qubit depending on its initial quantum state, either zero or one. Then the qubit is read out in the same way as before — with a laser.
“Only now, the emitted light reflects the absence or presence of the electron, and with almost 10,000 times more signal,” Glen said. “By converting our fragile quantum state into stable electronic charges, we can measure our state much, much more easily. With this signal boost, we can get a reliable answer every time we check what state the qubit is in. This type of measurement is called ‘single shot readout,’ and with it, we can unlock a lot of useful quantum technologies.”
“The ability to perform single shot readout unlocks a new opportunity: using the light emitted from silicon carbide qubits to help develop a future quantum internet,” Glen said. “Essential operations such as quantum entanglement, where the quantum state of one qubit can be known by reading out the state of another, are now in the cards for silicon carbide-based systems.”
“We’ve essentially made a translator to convert from quantum states to the realm of electrons, which are the language of classical electronics, like what’s in your smartphone,” Anderson said. “We want to create a new generation of devices that are sensitive to single electrons, but that also host quantum states. Silicon carbide can do both, and that’s why we think it really shines.”
References and resources also include:
https://www.sciencedaily.com/releases/2022/02/220202153853.htm
https://phys.org/news/2022-08-approach-quantum.html
https://phys.org/news/2024-02-techniques-qubits-erbium.html#google_vignette
