Tech giants like IBM, Google, Intel, and numerous startups are racing to develop the new machine that utilizes 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 efficiently solve problems 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 researches 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.
5. Rigetti 19Q
Rigetti 19Q superconducting processor
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.
4. Google Bristlecone
Bristlecone processor | Qubits with nearest neighbor connectivity are represented by symbol X
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.
In the next 5 years, Google is intended to achieve something they call “quantum supremacy” and facilitate the development of quantum algorithms on actual hardware. Bristlecone is scaled to a square array of 72 qubits, and it follows the physics of Google’s previous 9 qubits linear array technology.
3. Intel Tangle Lake
49-qubit quantum computing test chip | Tangle Lake
In January 2018, Intel announced a 49-qubit superconducting quantum chip, named Tangle Lake. It’s a 3* 3-inch chip that will let scientists improve error correction methods and simulate computational problems.
In addition, 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.
2. IBM Q
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 2 machines –
- 20-qubits superconducting quantum chip
- 50-qubits prototype that will be the basis of upcoming IBM Q systems.
Compared to previous quantum machines, the 20-qubits processor has nearly twice the coherence time. It has an average of 90 microseconds, whereas the previous generation quantum processor had an average coherence time of 50 microseconds. The system is developed to scale; a 50-qubits 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.
Read: Could We Be Performing Quantum Computing In Our Own Brain?
1. D-Wave 2000Q
Image credit: D-Wave
In 2017, D-Wave announced 2000Q quantum computer and open-source software, Obsolv, that solves quadratic unconstrained binary optimization problem 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 are using 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.
Read: A New Quantum Particle – 3D Skyrmion In A Quantum Gas
Considering D-Wave’s pattern of doubling performance every 2 years, the company may release a 4000-qubits quantum machine in 2019.
