Tech giants like IBM, Google, Intel, and numerous startups are racing to develop new machines that utilize quantum mechanical phenomena like superposition and entanglement. Quantum computing will be extremely useful to the next generation of computing and communication technology.
However, quantum computing is not going to come easily, and we don’t know anything for sure – when it will arrive and what exactly it will look like.
At present, dozens of companies and research institutes are trying to use different techniques to create the most powerful computer world has ever witnessed. It will be able to solve problems efficiently that aren’t possible on existing supercomputers.
The development of an actual quantum machine is in its infancy, but tons of experiments have been conducted in which quantum operations were performed on a small scale [small no. of qubits]. To learn more, you can read all the interesting facts and the latest research on quantum computing.
Below, we’ve listed all advanced quantum processor chips developed so far. Although a fully functional quantum computer is a long-term goal, these chips represent major milestones in efforts to the development of future computing technologies.
Table of Contents
11. QuTech Starmon-5
Qubits: 5 qb
In 2020, QuTech — a research institute for quantum computing and quantum internet — announced a 5-qubit quantum chip called Starmon-5. Based on circuit quantum electrodynamics, the chip contains 5 transmon qubits in an X-shaped coupling configuration.
In this chip, every qubit has a dedicated microwave-control line for one-qubit gating, a dedicated flux-bias line for two-qubit gating, and a dispersively-coupled resonator for readout.
The company plans to release a suite of software programs to make programming easier and more accessible for its first-generation quantum hardware.
10. Rigetti 19Q
Rigetti 19Q superconducting processor
Qubits: 19 qb
Rigetti Computing develops quantum integrated circuits and the “Forest” cloud platform to help coders write quantum algorithms. It’s a full-stack company that fabricates quantum chips, builds controlling architecture, and develops algorithms for the processors.
Their latest superconducting quantum processor has 19 fully programmable qubits. Recently, they demonstrated unsupervised machine learning using 19Q. They did this with their own classical/quantum hybrid algorithm for clustering.
The 19Q chip is currently available as a configurable backend in Forest. You can apply for access.
9. Google Bristlecone
Bristlecone processor | Qubits with nearest neighbor connectivity are represented by the symbol X
Qubits: 72 qb
Bristlecone is a new quantum processor developed by Google. It’s a gate-based superconducting system that provides a testbed for research related to qubit technology, machine learning, quantum simulation, and optimization.
Bristlecone is scaled to a square array of 72 qubits, and it follows the physics of Google’s previous 9 qubits linear array technology. It has high fidelity rates for readout (99%), single-qubit gates (99.9%), and two-qubit gates (99.4%).
Google has used Bristlecone’s technology to demonstrate quantum supremacy and investigate first and second order error-correction using the surface code. The goal is to explore near-term applications that are compatible with error-corrected quantum chips.
8. Intel Tangle Lake
49-qubit quantum computing test chip | Tangle Lake
Qubits: 49 qb
In January 2018, Intel announced a 49-qubit superconducting quantum chip named Tangle Lake. This 3*3-inch chip will allow scientists to improve error correction methods and simulate computational problems.
Intel also unveiled a neuromorphic research chip named Loihi, which mimics the operations performed in the human brain. The chip is developed with the objective of making deep learning more efficient.
Intel is also working on spin qubits in silicon. They are smaller than superconducting quantum bits and thus have a scaling advantage. They have already developed a spin qubit fabrication flow on 300-millimeter process technology.
7. IBM Q
Qubits: 50 qb
IBM Q was launched in 2017 as an initiative to develop commercial quantum computers for science and business. So far, they’ve built and tested two machines –
- 20-qubit superconducting quantum chip
- 50-qubit prototype that will be the basis of upcoming IBM Q systems.
Compared to previous quantum machines, the 20-qubit processor has nearly twice the coherence time. It has an average coherence time of 90 microseconds, whereas the previous generation quantum processor had an average of 50 microseconds. The system is developed to scale; a 50-qubit prototype yields similar performance.
They have also developed the Quantum Information Software Kit (QISkit) open for public use. It allows you to execute quantum circuit-based experimental programs on a quantum circuit simulator running on the Cloud or a laptop.
6. D-Wave 2000Q
Image credit: D-Wave
Qubits: 2,048 qb
In 2017, D-Wave announced 2000Q quantum computer and open-source software, Obsolv, that solves quadratic unconstrained binary optimization problems on both 2000Q and conventional hardware architectures
2000Q is the company’s follow-up to the 1000-qubits 2X. The jump from 1000 to 2048 qubits enables researchers to deal with larger quantities of data and more complex problems. According to the company, 2000Q can outperform conventional servers by factors of 1,000 – 10,000.
Temporal Defense Systems Inc. purchased 2000Q to solve critical and complex cybersecurity problems. Although they didn’t reveal the price, the machine is valued at $15 million.
While D-Wave’s computers use quantum mechanics for calculations, it is not clear if they will ever be able to solve real-world problems. For now, they are only suitable for solving optimization problems.
5. Google Sycamore
Qubits: 53 qb
In 2019, Google researchers claimed that they had achieved quantum supremacy with a newly developed processor named Sycamore. It’s a superconducting transmon quantum processor with 53 qubits.
It has been used in various complex calculations that are far beyond the limits of state-of-the-art- supercomputers. In 2020, for instance, researchers reported the largest chemical simulation on Sycamore. In 2021, a team of scientists realized the ground state of the toric code (topological quantum error correcting code) with 31 qubits. In 2022, Sycamore successfully simulated the traversable wormhole dynamics.
Jiuzhang performed a complex computation in 200 seconds. A state-of-the-art supercomputer would take approximately 2.5 billion years to perform the same computation. Credit: Hansen Zhong
Qubits: 76 qb
Developed by researchers at the University of Science and Technology of China, Jiuzhang is the first photonic quantum chip to achieve quantum supremacy (in 2020). Previously, Google’s Sycamore (which relies on superconducting materials, and not photons) claimed to have achieved quantum supremacy.
This processor has been able to carry out Gaussian boson sampling in 3 minutes 20 seconds, with 76 detected photons. It can yield an output state space dimension of 1043 and a sampling rate that is 1024 faster using the current simulation techniques on supercomputers.
3. IBM Eagle
Qubits: 127 qb
In November 2021, IBM revealed a powerful quantum chip based on the transmon superconducting qubit architecture. This is the first time IBM pushed quantum technology beyond the 100-qubit barrier.
The new processor uses a heavy-hexagonal qubit layout, in which qubits link with either two or three neighbors as if sitting upon the corners and edges of tessellated hexagons. This type of configuration reduces the chances of errors that may arise due to the interactions between adjacent qubits.
Like IBM’s previous quantum processors, Eagle features readout multiplexing. This allows scientists to decrease the number of electronics and wiring without significantly impacting the performance of a single qubit.
2. IBM Osprey
Qubits: 433 qb
IBM introduced its most powerful chip [Osprey] in Quantum Summit 2022, announcing major breakthroughs in quantum software and hardware. This prototype chip uses the ASIC (application-specific integrated circuit) design, which is more powerful and less bulky than previous FPGA (field-programmable gate array) designs.
The processor is made with 14-nanometer FinFET technology and operates at approximately 4 Kelvin. It consumes about 10 milliwatts per qubit (the previous generation processor, on the other hand, required 100 watts per qubit).
Osprey is capable of running complex calculations well beyond the computational capability of classical computers. To put this into perspective, the number of binary bits that would be required to represent a state of the Osprey chip far exceeds the total number of stars in the Universe.
1. D-Wave Advantage
Qubits: 5,760 qb
All processing units developed by D-Wave are based on quantum annealing. In 2020, the company released its 5th generation quantum processor named Advantage. It is built from the ground up with a new architecture with 5,000+ qubits and 15-way qubit connectivity.
Since Advantage has 2.5 times more connection and over twice the number of qubits than D-Wave’s previous processor (2000Q), it can solve bigger and more complex business problems. More specifically, it can solve real-world problems with up to 1,000,000 variables and 100,000 constraints.
More to Know
What is a qubit?
Classical computers store and process data using (binary) bits, which can be either 1 or 0. A quantum computer, on the other hand, can store and process data using a quantum bit (short for qubits). Qubits can be either 0, 1, or a linear combination of two states.
Unlike binary bits, qubits can exist in superposition states, be entangled with other qubits, and even be subjected to incompatible measurements. These properties make qubits far more complex and more powerful than binary bits.
In simple terms, qubits are the quantum mechanical analog of classical bits.
Several tech giants, especially IBM and Google, are heavily investing in quantum technology. The goal is to develop a super-efficient combination of hardware and software that solve complex real-world problems. Advancements made to date show that quantum machines can be used in
- Weather forecasting
- Financial modeling
- Electronic materials discovery
- Drug design and development
- Traffic optimization
- Cybersecurity and cryptography
What’s the future of quantum computing?
According to the Precedence Research report, the global quantum computing market size will reach $125 billion by 2030, growing at a CAGR of over 36.8% from 2023 to 2030.
The early adoption of quantum technology in the banking and finance sector is more likely to fuel this growth. The demand for quantum machines is increasing in other fields as well, including machine learning, healthcare, material science, chemicals, and aerospace and defense.