Quantum Computing Circuits: The Road Ahead for Moore’s Law

The invention of the computer with semiconductor chips as the core has achieved the rapid development of the modern information technology industry (hardware, software, network, communication, etc.), and profoundly changed the form of human social activities.

As Moore’s Law slows, chips are moving toward complex system-level innovations to meet power and performance requirements. One direction that is particularly compelling is that the once dreamed quantum computing is now becoming a reality. Quantum computing is the inevitable result of chip size breaking through the limits of classical physics. It is a landmark technology in the post-Moore era, and the trend of quantization of information is inevitable.

Fundamentals of Quantum Computers

Quantum computers use quantum superposition and quantum entanglement to perform encoding, logical operations, storage, and processing of information. The core of this is the coherence from quantum, which is on the physical level. Classical computers will never There may be such coherence.

Quantum superposition means that a qubit has two states of 0 and 1 at the same time, expressed as α|0+β|1, where |α|2+|β|2=1, and its realization forms include different polarization states of photons, nucleons and electrons. Spin, the state of motion of electrons around a single nucleus, current charge in superconductors, etc. Quantum entanglement allows a qubit to share its state with other spatially independent qubits, creating a super-superposition that enables quantum parallel computing, whose computing power can grow exponentially as the number of qubits increases.

Qubits can form quantum logic gates, which have the following characteristics for single-bit quantum logic gates: single-bit quantum logic gates can be represented by a 2×2 matrix; this matrix must be unitary, and unitary is the only restriction; any 2 The unitary matrix of ×2 constitutes a quantum gate; the types are divided into X, Y, Z, Hadamard gate and so on. Double-bit quantum gates include CNOT gates, SWAP gates, etc.

The working state diagram of the overall quantum system is as follows:

The meaning of quantum computer and quantum supremacy

From the Shor algorithm in the last century (solving the factorization problem of large numbers, it can quickly crack the RSA key commonly used in classical encryption, from which the quantum algorithm comes from), Grover search algorithm (can be used for database search), to HHL in recent years Algorithms (for quantum machine learning, from financial transactions to traffic planning to plasma simulation, etc.), a variety of quantum algorithms emerge in an endless stream. In addition, quantum systems also play an important role in biopharmaceutical chemical analysis and even energy. significance. The figure below is a market share map that McKinsey assesses that quantum computing can contribute to various industries, which can be seen.

The most talked about quantum computer is quantum hegemony, which refers to the computing power possessed by quantum computing that surpasses all classical computers. Taking a recent scientific and technological progress as an example, for the molecular dynamics simulation of the metabolic reaction of ferredoxin in photosynthesis, a quantum computer is used to reduce the computational complexity from O(N 11) to O(N 3) , reducing the time required from 24 million years to one hour!

At the same time, since quantum calculations are all reversible unitary calculations (unitary operator), that is to say, only at the end of a quantum calculation (when measuring the quantum state) will the entropy increase. This would drastically reduce the energy consumed by quantum computing itself.

These huge advantages have made quantum technology one of the most concerned scientific and technological advances. List the Nobel Prizes related to quantum technology in recent years: (Quantum coherence) In 2005, “Contribution to the quantum theory of optical coherence” and to Development of laser-based precision spectroscopy. (Single Quantum Manipulation) 2012, “A pioneering experimental method capable of measuring and manipulating single quantum systems”. (Topological Quantum Computing) In 2016, the topological phase transition and topological phase of matter were theoretically discovered. Roger Penrose, winner of the 2020 Nobel Prize in Physics, proposed that the quantum coherent processing of information by the brain is a kind of “quantum computing”.

However, the application of quantum computing places high demands on physical systems. Qubits are very fragile. Unlike mos transistors, which can be easily integrated into chips, quantum systems often require extremely low temperatures, very fine control, and sufficient isolation from the environment. This puts forward technical requirements for computing circuits in the current working environment of quantum systems.

Advanced progress of world science and technology enterprises

Quantum technology has always attracted the attention of scientific and technological workers and enterprises all over the world. Typical start-up companies in the field of quantum computing are mainly dominated by European and American countries.

The quantum two-state (two-level) solid systems used by different companies are also different. At present, the carrier usage of quantum computing by major international companies is as follows: Google and IBM have chosen more mainstream superconducting quantum circuits; Intel uses silicon quantum dots; Microsoft And Bell Labs use topological qubits; quantum computing start-up ionQ chooses ion traps; Quantum Diamond Technologies uses diamond vacancies.

Google & D-Wave

In May 2013, Google announced the purchase of D-Wave for $15 million. In September 2014, Google announced the construction of ultrafast quantum chips based on superconducting electronics. In August 2015, Google announced that D-Wave’s D-Wave Two 512-bit quantum chip had come out. In January 2017, D-Wave announced their new commercial quantum computer with 2,000 superconducting qubits. The 72-bit superconducting qubit chip shown by Google in March 2018.


In October 2017, Intel announced the delivery of a 17-qubit superconducting test chip to its Dutch partner QuTech. In January 2018, Intel announced at the Electronics Show (CES) that it had started manufacturing and delivering 49 qubit superconducting quantum chips. In April 2020, Intel, in cooperation with QuTech, demonstrated in nature the successful control of “hot” qubits at temperatures above 1K. With a fidelity of up to 99.3%, these breakthroughs highlight the low-temperature control of future quantum systems and the potential of silicon spin qubits in integrated packages that closely resemble single-electron transistors. In December 2020, Intel launched the second-generation low-temperature control chip Horse Ridge II, which supports enhanced functions and higher levels of integration to achieve elegant control of quantum systems. New functions include manipulating and reading the state of qubits, with control The potential for multiple gates needed to entangle multiple qubits.

At the meeting of the American Physical Society (APS) in March 2022, Intel introduced the results of the company’s latest 14 papers and revealed the company’s quantum strategic plan. In Intel’s view, there is still a long way to go for practical quantum computing in the future, which may last for about ten years, so they do not plan to provide NISQ-oriented application products. As a leader in classical computing microprocessors, Intel has developed a long-term roadmap around the development of quantum computing-related engineering complexities: it is committed to providing powerful quantum processor chips and error correction functions for the future.

Intel says its biggest advantage in the quantum computing race is its ability to use silicon transistors to build high-performance computing modules. Compared with superconducting qubits, spin qubits have significant advantages. For example, the die area of each qubit is reduced by several orders of magnitude, and based on spin qubit technology, Intel can produce the chip through its own chip fab. , without the need to install new manufacturing equipment.

Unlike other teams that use electron beam lithography, atomic layer deposition, and lift-off silicon processors, Intel uses advanced standard EUV (extreme ultraviolet) optical lithography, plasma etching, CMP (chemical mechanical polishing), and large-scale 193nm The photolithography process builds silicon-based spin qubit chips. Intel’s advanced manufacturing methods have the advantages of high yield, high precision, low pollution, high uniformity, and high reproducibility.

At present, Intel has developed its own software development kit (SDK), C++ compiler and system software workflow with LLVM architecture, aiming at efficiently executing classical/quantum variational algorithms. Among them, the optimized compiler can take over the user program and compile it into the original gate set of the processor in the most efficient way, thereby controlling all interactions between the classical processor and the quantum processor to achieve efficient cooperation. The SDK supports users to develop quantum dot chips like developing some different simulators. Meanwhile, Intel’s software team is also working on how to run these algorithms on spin qubit-based quantum processors.


IBM released the IBM Quantum Experience quantum cloud computing with 5 qubits in May 2016, and announced in May 2017 that it has built a 16-qubit Quantum Experience general-purpose computer and a 17-qubit commercial processor prototype. In November 2017, IBM announced that it has successfully built a prototype of a 50-qubit quantum computing processor, which will be used in the next-generation IBMQ system and provided to customers. Announced in December that it will partner with 12 major companies, including Samsung, JPMorgan Chase and Barclays, to develop commercial quantum computing.

At the 2019 International Consumer Electronics Show (CES), IBM launched the world’s first quantum computing all-in-one machine, Q System One, calling it “the world’s first integrated general-purpose approximate quantum computing system designed for scientific and commercial purposes.” IBM believes that measuring the performance of a quantum device not only depends on the number of qubits, but also considers the connectivity of the qubits (Connectivity), the measurement error of the gate (Measurement Errors), the increase of the coherence time (Coherence Times), the device crosstalk ( The reduction of Device Crosstalk, and the improvement of software to circuit compilation efficiency (Compiler Efficiency) and other aspects, so IBM proposed a new metric for quantum systems – Quantum Volume (Quantum Volume).

In August 2020, IBM stated that its latest 27-bit qubit system Montreal reached 64QV; only 4 months later, Jay Gambetta, vice president of quantum computing at IBM, announced on Twitter that its latest quantum computing system IBM Q System One-Montreal It has reached 128QV, double that of four months ago. Rapid rollout of the new system, thanks to hardware design improvements and a new “Target Rotary” pulse technology that increases the fidelity of the two quantum entanglement operations while reducing errors in adjacent qubits . In August of the same year, IBM released: the Falcon chip containing 64 qubits.

In May 2022, IBM updated its quantum computing roadmap, planning to create a new quantum processor and quantum software and service model, so as to realize the next generation – a quantum-centric supercomputer, and around the quantum processor, CPU New resources combined with GPUs to solve some of the world’s most challenging problems.

To achieve the ultimate goal of building a quantum-centric supercomputer, IBM must address several challenges in its roadmap: 1. Extend the use of dynamic circuits. Because dynamic circuits require a control system that allows data to move with low enough latency to be processed in real time, IBM had to design a third-generation control system to meet the low-latency requirements. 2. new language. IBM needed to develop a new language that would allow users to describe the combination of real-time classical computation and quantum gates. With help from the quantum community, IBM is working to develop an OpenQASM 3 language for describing new circuits. 3. New compiler technology. IBM needed to develop new compiler technology to convert the OpenQASM 3 circuitry into a form that would allow it to run on the control system. 4. Fault Tolerant Quantum Computing. To successfully scale to hundreds of thousands of qubits, IBM will have to have quantum error correction capabilities.

Domestic quantum circuit progress

In terms of enterprises, in August 2015, the Chinese Academy of Sciences-Alibaba Quantum Computing Laboratory was established in Shanghai. In December 2017, Tencent’s long-planned quantum laboratory was exposed. In December 2017, the Beijing Institute of Quantum Information Science was established in Beijing Zhongguancun Software Park, aiming to promote China to seize the commanding heights of global quantum information technology. Xue Qikun, an academician of the Chinese Academy of Sciences, was elected as the president of the institute. In March 2018, Baidu announced the establishment of the Institute of Quantum Computing to conduct business research on quantum computing software and information technology applications.

In terms of scientific research, in August 2016, the Micius quantum science experimental satellite was successfully launched in Jiuquan with the Long March 2D carrier rocket. In June 2017, China took the lead in realizing quantum entanglement distribution at the thousand-kilometer level by using the Micius quantum science experimental satellite. In 2021, the 66-bit programmable superconducting quantum computing prototype “Zu Chongzhi 2.0” developed by the Chinese Academy of Sciences came out. By manipulating 56 qubits on it, it realized the superiority of quantum computing in random line sampling tasks. The upgraded version of the optical quantum computing prototype “Jiuzhang 2.0” developed later has partial programmable capabilities for the Gaussian Bose sampling problem. It can complete the task in one minute, and the most powerful supercomputer currently takes hundreds of millions of years. time.


After nearly 20 years of development, superconductivity and its solid-state quantum coherent circuits have developed from the demonstration of simple physical phenomena to the stage that requires the intervention of microelectronics engineering technology.

The problems that need to be continuously paid attention to and solved in the future mainly focus on the following aspects: 1. Further develop the basic theory to solve the problem of quantum coherence. 2. Physical reliability analysis and engineering technical problem assessment of circuit large-scale integration. 3 Hardware design and circuit design for the realization of the basic theory of quantum computing. 4 Optimize the design of error-tolerant quantum error-correcting codes according to the characteristics of superconducting circuits. 5 Using the diversity design of superconducting qubits to establish a topological quantum computing model. 6 Establishment of major problems in quantum simulation, annealing, machine learning, Bose sampling, etc. 7 Storage of information.

Major powers in the world today have invested heavily in the research and development of quantum computing. This field has broad prospects. It is of extraordinary significance in terms of the country, economy, technology, military, and security. I hope that in the future, relevant The fantasy of quantum computing turned into a truly disruptive technology!