# Research Trends in Quantum Computers by Focusing on Qubits as Their Building Blocks

^{*}

## Abstract

**:**

## 1. Quantum Technology

## 2. Quantum Computer Hardware

#### 2.1. Superconducting Qubits

^{α}) in their energy relaxation times T

_{1}[20,21,22].

#### 2.2. Trapped Ion Qubits

^{6}, which is higher than other qubits, such as superconducting qubits (~1000) or Rydberg atom qubits (~200) [31,32]. Another advantage is that trapped ions allow for high-fidelity implementation of single- and two-qubit gates. Single-qubit rotations have achieved fidelities up to 99.9999%, surpassing other modalities. Two-qubit gates have been demonstrated with fidelities up to 99.9% for hyperfine qubits and 99.6% for optical qubits, with only superconducting qubits achieving comparable performance [33,34,35,36]. Trapped ions benefit from being fundamentally identical, ensuring that addressing each ion requires the same frequency, resulting in improved reproducibility of the qubits and fewer calibration steps. This contrasts with superconducting qubits, which have varying frequencies and coherence times due to the fabrication process’s variability and thermal cycling [21]. Trapped ions have the highest coherence time to gate operation ratio; however, their absolute gate speeds are slower than some other qubits. Two-qubit gates for trapped ions have been demonstrated as fast as 1.6 µs, while superconducting qubits can perform them in tens of nanoseconds [30]. Trapped-ion-based quantum computation may take considerable time, depending on the number of operations required. Even with optimistic but achievable gate and readout parameters, factoring a 1024-bit and 2048-bit number using a trapped-ion-based quantum computer could take up to ~10 and ~100 days, respectively [37,38]. Trapped-ion quantum processors face challenges due to long gate times, hindering quantum simulations or calculations. Achieving “quantum supremacy” may be difficult if a classical computer’s gate speed greatly exceeds that of a trapped-ion quantum processor. One promising research area is performing entangling gates using sequences of ultrafast pulses or shaped pulses of continuous-wave light. However, sub-microsecond gate fidelities have not exceeded 76% [37,39].

#### 2.3. Neutral Atom Qubits

#### 2.4. Other Types of Qubits

- Semiconductor qubits: the field of semiconductor qubits is quite diverse, encompassing various systems, materials, and techniques. The semiconductor qubits demonstrated so far differ from each other in many ways. They range from systems that operate at mill kelvin temperatures, which can only be achieved inside dilution refrigerators, to systems that are suitable for room-temperature operation. They can be artificially engineered potential wells that confine quantized electronic states or single-atom impurities in a lattice. They exploit nuclear or electronic degrees of freedom. Despite these differences, however, they share specific properties, such as the potential for high-density integration on a large scale. This feature arises from the well-established nanofabrication technology of the semiconductor industry [53].
- Nuclear magnetic resonance (NMR) qubits: While nuclear magnetic resonance (NMR) has demonstrated impressive control, it is not a practical candidate for quantum computers due to scalability issues. As the number of qubits grows beyond a dozen, the ratio of gate time to decoherence becomes too small. Therefore, there is a need for other technologies that can handle larger systems.
- Topological qubits: Topological qubits utilize anyons, which are exotic quasiparticles. Anyons have unique properties in fundamental physics as they generalize the statistics of bosons and fermions. Due to their exotic statistical behavior, they exhibit non-trivial quantum evolutions described by their topology. This means that they are abstracted from local geometrical details. When anyons are used to encode and process quantum information, this topological behavior provides much-desired resilience against control errors and perturbations [54].
- Molecular spins: Artificial magnetic molecules can contribute to the achievement of large-scale quantum computation by (a) integrating multiple quantum resources and (b) reducing the computational cost of some applications. Chemical design, guided by theoretical proposals, facilitates the embedding of nontrivial quantum functionalities in each molecular unit, which then act as a microscopic quantum processor able to encode error-protected logical qubits or to implement quantum simulations. Scaling up even further requires “wiring-up” multiple molecules. Recently, this goal was achieved by coupling to on-chip superconducting resonators. The potential advantages of this hybrid approach and the challenges that still lay ahead have been critically reviewed. Figure 4 demonstrates the molecular structures of three molecular spin qubits and the scaling-up process [55].

## 3. Looking Ahead

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 1.**Unimon qubit and its measurement setup. (

**a**) Superconducting-qubit types; (

**b**) Schematic unimon circuit; (

**c**) Distributed-element circuit model of the unimon; (

**d**) Schematic illustration of a mechanical inverted pendulum system; (

**e**) False-color microscope image of a silicon chip containing three unimon qubits; (

**f**) Simplified experimental setup used to measure the unimon qubits at 10 mK. Reproduced from Ref. [29].

**Figure 2.**Photonic links use probabilistic, heralded entanglement, which is generated from the interference of emitted photons from each module. (

**a**) Photonic links use probabilistic, heralded entanglement which is generated from the interference of emitted photons from each module; (

**b**) Linking modules using ion qubit transport. Reproduced from Ref. [40].

**Figure 3.**Platform for trapping and addressing atomic qubits. (

**a**) Experimental layout for trapping and addressing atomic qubits; (

**b**) Atomic level diagram and wavelengths used for cooling, trapping, and qubit control; (

**c**) Averaged atomic fluorescence image of the 49 site array with spacing 3 µm; (

**d**) Global microwave Rabi rotations on a block of 9 qubits at 76.5 kHz; (

**e**) A Ramsey experiment with microwave π/2 pulses and the focused 459 beam providing a RZ(θ) rotation on a single site; (

**f**) parity oscillation of a 2-qubit Bell state created using a CZgate. Reproduced from Ref. [51].

**Figure 4.**(

**a**) Molecular structures of three molecular spin qubits. In the first two, the qubit is encoded in the states of a spin S = 1/2. For HoW

_{10}, it is defined by the tunnel split states arising from the m = ±4 total angular momentum projections. (

**b**) Illustration of scaling up by a global frequency addressing and by a local addressing with switchable qubit-qubit interactions. Reproduced from Ref. [55].

Institutions | Projects |
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Massachusetts Institute of Technology | |

Harvard University | |

Max Planck Society | |

Princeton University | |

University of Tokyo |

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**MDPI and ACS Style**

Dejpasand, M.T.; Sasani Ghamsari, M.
Research Trends in Quantum Computers by Focusing on Qubits as Their Building Blocks. *Quantum Rep.* **2023**, *5*, 597-608.
https://doi.org/10.3390/quantum5030039

**AMA Style**

Dejpasand MT, Sasani Ghamsari M.
Research Trends in Quantum Computers by Focusing on Qubits as Their Building Blocks. *Quantum Reports*. 2023; 5(3):597-608.
https://doi.org/10.3390/quantum5030039

**Chicago/Turabian Style**

Dejpasand, Mohamad Taghi, and Morteza Sasani Ghamsari.
2023. "Research Trends in Quantum Computers by Focusing on Qubits as Their Building Blocks" *Quantum Reports* 5, no. 3: 597-608.
https://doi.org/10.3390/quantum5030039