On May 8th, Alibaba Quantum Lab's team announced that it has successfully developed the world’s most powerful quantum circuit simulator, called “Taizhang”, in recent days. Based on the powerful computing power of the Alibaba Group Computing Platform online cluster, Chapter 'The world's first successful simulation of 81 (9x9) bits and 40 layers of Google's random quantum circuit as a benchmark, the simulator that previously reached this layer can only handle 49 bits.
Quantum hegemony seems to be playing a 'relay battle'.
In February, IBM demonstrated its 50 qubit prototypes to the outside world, and the internal structure chart was also exposed.
In March, Google announced the 72-bit qubit processor Bristlecone.
At the end of March, Microsoft found strong evidence of the presence of angel particles, Majorana fermion, and it is expected that the working qubits will be available by the end of the year.
Now it's time for Ali to play.
On May 8, the team of Alibaba Quantum Labs announced that it has successfully developed the world’s strongest quantum circuit simulator, named “Taizhang”, in recent days.
Based on the powerful computing power of the online cluster of Alibaba Group Computing Platform, 'Tai Zhang' was the first in the world to successfully simulate a Google random quantum circuit with 81 (9x9) bits and 40 layers as the benchmark. Previously this simulator reached this layer only Can handle 49 bits.
At the same time, this simulation task only uses 14% of the computing resources of the Alibaba Computing Platform online cluster. The 'Taizhang' innovative algorithm has a very low overhead and can take full advantage of the platform's online clustering. It cannot be done on supercomputers in the past. Simulation tasks, such as 64 (8x8) bit 40-layer simulation, 'Tai Zhang' can be completed in 2 minutes.
Alibaba 'Taizhang' simulator compares the results of the current Google's random circuit with the main simulator emulating the random circuit of Alibaba 'Taizhang' simulator compared with the results of the current main simulator emulating Google Random Circuit's 'Taizhang' simulation of a random quantum circuit scale Compared with the scale that Google quantum hardware can achieve
Quantum computing may overturn the current computing technology and is a hot topic in the scientific and industrial research. However, the realization of quantum computing is very difficult. At present, the high-precision quantum processor that has been implemented has only a few qubits. Therefore, the scale is slightly larger. The quantum algorithm has no carrier yet to run.
The role of the simulator is to 'keep it up and down', down to help understand, to design the hardware, to carry forward the exploration and verification of algorithms and applications. 'Taizhang' for the first time makes testing and verification known as 'moderate' 50-200 bit The quantum algorithm becomes possible, thus providing a powerful tool for assisting in the design of medium-scale quantum algorithms, quantum software, and even quantum chips.
In a typical quantum circuit simulation scheme, it is necessary to store the full amplitude of the quantum state and simultaneously simulate the quantum operation on the massive data. This method requires the constant exchange of data among numerous computing nodes, causing a huge communication overhead. Therefore, in the past, Such simulation tasks are often performed on supercomputers.
The laboratory team, based on another simulation scheme proposed by Prof. Shi and its collaborator Igor Markov in 2005, invented a simple and effective method to decompose the entire simulation task, and then allocated these subtasks to different computing nodes in a well-balanced manner. The communication overhead of 'Taizhang' is extremely small, which makes it very suitable for distributed computing platforms.
The reference random quantum circuit is Google's algorithm proposed to achieve 'quantum hegemony'. 'Quantum hegemony' refers to the extent to which the quantum processor's size and precision have arrived cannot be simulated by classical calculations. Google proposed future work in March this year. Goal: 72-bit high-precision quantum processor. The result of 'Tai Zhang' shows that this planned processor is still not enough to achieve quantum hegemony if only the benchmark algorithm is run.
The research results are also submitted to the preprinted website arXiv. The article is tied with the first author for Quantum Lab Quantum Scientist Dr. Chen Jianxin and intern Zhang Fang, the author and intern Huang Jiachen and Dr. Michael Newman.
Alibaba Quantum Lab is a lifelong professor at the University of Michigan and Shi Quan, a world-renowned quantum scientist. He is the chief quantum scientist and the director of Quantum Labs. He was the winner of two Georgel Prizes for the highest theoretical computer and Mario Seg, a Hungarian-American computer scientist. Mario Szegedy also joined the lab earlier this year. The lab is in a period of rapid growth in the introduction of talent.
In 2016, Google proposed a scheme for realizing quantum hegemony by implementing a specific random quantum circuit on a qubit corresponding to a two-dimensional array MxN. This type of specific random quantum circuit is often called a quantum hegemonic circuit. In the scheme, When the number of bits (MN) on the two-dimensional array reaches 50, the depth (number of layers) of the circuit reaches 40 or so, and the most powerful supercomputer in the world cannot effectively simulate such a circuit.
Google’s hardware team hopes to achieve such a hegemonic circuit by maintaining a 1% read error, a 0.1% single-bit gate error, and a 0.6% two-bit gate error in a 9-qubit 1D array to a larger scale quantum system. And through this specific task, quantum hardware is surpassed by the world’s most powerful classical computing resources. Since then, several research teams have simulated these circuits on different supercomputers. Before, the world’s best research results Not yet reached 50 bits and 40 layers at the same time.
In the current model of quantum computing, there is a quantum circuit model in which information is stored in qubits and is calculated by a quantum gate that resembles a classical logic gate. Quantum scientist Chen Jianxin and an intern at the Boomerang Quantum Lab team Zhang Zhangfang implemented a distributed-based universal quantum circuit simulation scheme, and tested the first version of Google's random quantum circuit based on the research simulator.
A small amount of computational resources (around 14%) using online clustering of Alibaba Computing Platform was successfully used by the laboratory team to simulate 9x9x40, ie 81-bit 40-layer random circuits using the 'Taizhang' simulator, and successfully simulated separately.
A 100-bit, 35-layer (10x10x35), 121-bit, 31-layer (11x11x31) and 144-bit, 27-layer (12x12x27) random quantum circuit.
At present, there are two mainstream simulation schemes in the industry. One is to store all the amplitudes of the quantum state. The other is to quickly calculate the results for any amplitude. The first type of simulation scheme is basically implemented in a supercomputer because of storage. The quantum state of the bit requires a Petabyte-level memory. When storing such a large amount of data, the quantum state is operated and calculated, and the data needs to be continuously exchanged between different computing nodes. Such communication overhead is common cloud service. Unsustainable.
On the online cluster of the Alibaba Computing Platform, the laboratory team used a second type of simulation program to calculate the arbitrary amplitude quickly and efficiently. After the task is split, the subtasks can be allocated to different nodes fairly evenly, with very little communication overhead. Enables the simulator to fit the cloud computing platform that is now widely available for service.
Prior to the results of this study, no research team has been able to successfully simulate the first generation of random test circuits with more than 50 bits and 40 layers in the world for the two simulation schemes. Each simulator can also be used in the simulator of the Boomerang Quantum Laboratory team. Calculate an amplitude of a 64-bit, 40-layer random circuit in minutes. The results of this research have also been submitted in the form of a paper on the preprinted website arXiv. The article is tied with the first author Quantum Scientist Quantum Scientist Chen Jianxin and the intern Zhang Fang, author also There are interns Huang Jiachen and Dr. Michael Newman.
The results of this research arXiv paper link: https://arxiv.org/abs/1805.01450
Google, IBM, Microsoft Quantum Hegemony, Shi Jie: Superconducting VS Ion Trap, Quantum Computing Entering the Bipolar World
In March of this year, at the annual meeting of the American Physical Society in Los Angeles, Google demonstrated a new quantum processor, Bristlecone. This gate-based superconductivity system aims to study the systematic error rate and scalability of quantum bit technology, and Quantum simulation, optimization and application in machine learning.
Julian Kelly, a research scientist at Google Quantum AI Labs, introduced in the article published by Google Researcher. Bristlecone follows the physics principle of the linear array technology of the nine qubit quantum computers proposed by Google. The best results shown by the technology are as follows: :
Low reading error rate (1%), single qubit gate (0.1%) and most important double qubit gate (0.6%).
The device uses the same pattern as the nine qubits for coupling, control, and readout, but expands it to a square array of 72 qubits.
Google researchers calculated that the goal of quantum hegemony can be perfectly proved by using 49 qubits, a circuit depth of more than 40, and a 2-bit error of less than 0.5%.
There are views that Google announced the 72-bit qubit processor because the quantum hegemony road encountered the rival IBM.
In November 2017, IBM announced the successful construction and measurement of 50 qubit prototypes with similar performance metrics. In February of this year, it also revealed its internal structure.
The 50 qubits are generally considered to be tasks that cannot be accomplished by ordinary supercomputers. IBM's move is also a landmark step in Quantum Hegemony.
Because both Google and IBM's quantum processors implement quantum computing via superconductivity, the two companies are chasing after one another in quantum hegemony.
But another force may also break out at any time. That is Microsoft.
Microsoft is betting on topological quantum computing. Although no interworking qubits have yet been made, quantum hardware and quantum computer software development kits have been developed.
The logic of Microsoft is that although Google and IBM have all made quantum bits, these are inexact qubits, and tiny vibrations or energy from the external environment can cause calculation errors.
Microsoft's topological quantum computer may be able to greatly reduce the noise. Julie Love, Microsoft's director of business development for quantum computing, once said: 'One of our qubits will be as powerful as 1,000 or even 10,000 noisy qubits.' They think that Microsoft Will get a working qubit before the end of this year.
An article published by Shi Zhi in February this year on Xinzhiyuan also mentioned that the first topological qubit in the universe will erupt this year, and Microsoft is likely to make it.
The facts also prove that Microsoft is also a step closer to quantum hegemony.
At the end of March this year, Microsoft researchers observed considerable evidence of the presence of Mayorana Fermi, known as the 'Angel Particle': electrons split into half-parts in their wires.
If Microsoft wants to build a working quantum computer, this will be crucial.
In addition, ion trap quantum computing may be able to hold a 50-60 bit bit weapon in the second half of this year. Shi Yong believes that the biggest winner in this field is Amazon and Facebook, which do not have stable quantum bits. Quantum computing will enter the bipolar world. era.