Google’s Sycamore: Exploring the Power of Google’s Quantum Computer
Quantum supremacy is a significant concept in quantum computing. It’s the stage at which a quantum computer can perform calculations that are beyond the reach of even the most powerful classical computers.
Google’s Quantum Computer, Sycamore, has achieved this milestone. In collaboration with NASA and Oak Ridge National Laboratory, Google demonstrated that Sycamore could compute in seconds what would take the largest and most advanced supercomputers thousands of years. This achievement is considered a breakthrough in the field of quantum computing.
The test involved running random quantum circuits on both quantum processors and traditional supercomputers. Getting results from a random quantum circuit is challenging without a quantum processor. Theory suggests that tasks beyond a certain size may be impossible to process, even on the largest imaginable supercomputer.
The quantum processor and supercomputer were tasked with computing increasingly complex and random circuits until the supercomputer couldn’t process them. At a certain point, even with all the tricks used by NASA’s quantum computing and supercomputing experts, the simulated “computer within a computer” couldn’t handle the random circuits given to it. This became the benchmark for Google’s quantum computer to surpass.
It’s important to note that achieving quantum supremacy means that the quantum computer has been able to do one thing faster, not everything faster. This achievement is the first step toward a future where quantum computers could potentially be used to support space missions, make mission schedules more efficient, and support the design of light and robust materials for modern spacecraft.
Speed
The speed of Google’s Sycamore quantum computer is truly impressive. It can perform calculations at a rate that far outstrips that of traditional supercomputers.
Sycamore completed a specific task in just a few seconds, a task that would take the world’s most powerful supercomputer, the Frontier, over 47 years to complete. This is due to the unique properties of quantum computing, where quantum bits (or qubits) can represent multiple states at once, unlike classical bits that can only represent a 0 or a 1. This allows quantum computers to process a vast number of possibilities simultaneously.
The specific task that demonstrated this speed was a complex, synthetic benchmark called random circuit sampling. This test involves taking readings from randomly generated quantum processes, which maximizes the speed of critical actions and reduces the risk of outside noise interfering with the calculation.
However, it’s important to note that this doesn’t mean that quantum computers are faster than classical computers at everything. The tasks that quantum computers excel at are very specific and often involve computations that take advantage of their quantum nature.
Qubits
Qubits, or quantum bits, are the fundamental units of information in quantum computing. Unlike classical bits, which can be either 0 or 1, qubits can represent both states simultaneously thanks to a property known as superposition. This allows quantum computers to process a vast number of possibilities at once, leading to faster computation times for certain tasks.
Google’s Sycamore quantum computer operates with 53 qubits. However, the latest system run by Google has a total of 70 operational qubits This large number of qubits allows Sycamore to perform complex calculations much faster than traditional computers.
The power of qubits comes from their ability to create and manipulate quantum states that scale exponentially with the number of qubits. This is due to another quantum property called entanglement, where the state of one qubit becomes linked with the state of another. When qubits are entangled, the information of one qubit can be instantaneously transferred to another, no matter the distance between them, leading to faster information processing.
However, working with qubits is challenging due to quantum noise, which can lead to errors in calculations. Despite these challenges, the development and operation of quantum computers like Sycamore represent a significant advancement in the field of quantum computing.
Benchmark Test
The benchmark test used by Google’s team for their Sycamore quantum computer is known as “random circuit sampling”. This is a complex, synthetic benchmark that is designed to test the speed of critical actions in a quantum computer and reduce the risk of outside noise interfering with the calculation.
Random circuit sampling involves taking readings from randomly generated quantum processes. This randomness is key because it maximizes the speed of critical actions and minimizes the risk of outside noise affecting the calculation. The randomness also ensures that there is no structure in the quantum circuits that classical algorithms can exploit, making it a fair test of a quantum computer’s capabilities.
The test generates millions of random numbers, but with slight statistical biases that are a hallmark of the quantum algorithm. Each run of a random quantum circuit on a quantum computer produces a bitstring, for example, 0000101. Due to quantum interference, some bitstrings are much more likely to occur than others when the experiment is repeated many times.
However, finding the most likely bitstrings for a random quantum circuit on a classical computer becomes exponentially more difficult as the number of qubits (width) and number of gate cycles (depth) grow This makes random circuit sampling a very effective benchmark for demonstrating the capabilities of a quantum computer.
In Google’s experiment, the Sycamore quantum computer managed to perform the random circuit sampling in mere seconds, whereas it was estimated that the world’s fastest supercomputer would take over 47 years to produce a similar output This clearly demonstrated the superior speed and computational power of the Sycamore quantum computer.
More
Quantum Noise: Quantum noise refers to the inherent fluctuations and instabilities that occur in a quantum computer during its operation. These fluctuations can impact the processes as they’re running and sometimes lead to new phases or states in a quantum system. Working through this noise to correctly record the states of quantum bits (qubits) is essential in getting quantum computers functioning properly. The experiments conducted on Google’s Sycamore quantum computer provide valuable insights into how quantum noise can impact processes as they’re running.
Software and Hardware: Google Quantum AI is actively developing tools that allow researchers to operate beyond the capabilities of classical computers. They have designed specific software and hardware for constructing novel quantum algorithms. These algorithms aim to help solve near-term applications for practical problems. The goal is to build scalable quantum computers that enable us to solve problems that would otherwise be impossible.
Cirq: Cirq is a Python library developed by Google. It allows users to write, manipulate, and optimize quantum circuits. These circuits can then be run against quantum computers and simulators. Cirq provides useful abstractions for dealing with today’s noisy intermediate-scale quantum computers, where the details of the hardware are vital to achieving state-of-the-art results.
OpenFermion: OpenFermion is an open-source library that helps compile and analyze quantum algorithms. These algorithms are used to simulate fermionic systems, including quantum chemistry. OpenFermion provides everything from efficient data structures for representing fermionic operators to fermionic circuit primitives for execution on quantum devices.
TensorFlow Quantum: TensorFlow Quantum (TFQ) is an open-source library for hybrid quantum-classical machine learning. TFQ allows for rapid prototyping of hybrid models. The library integrates quantum computing algorithms and logic designed in Cirq and is compatible with existing TensorFlow APIs.
Quantum Computing Service: Google’s Quantum Computing Service provides customers with access to Google’s quantum computing hardware. Programs that are written in Cirq can be run on a quantum computer in Google’s quantum computing lab in Santa Barbara, CA. This service is currently only granted to those on an approved list. No public access to the service is available at this time.
