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Precision Thermal Metrology; Analyzing Google’s “Quantum Supremacy” Claim through Actor-Network Theory

Madeleine Mary Cotter

Published May 7, 2026• 0 citations
Publisher

Abstract

Advanced computing technology is continuously demanding new materials, and the ultra-low temperature regime has become a point of interest in many fields, especially quantum computing. Quantum computing is an emerging field, hoping to leverage quantum mechanics to solve problems that traditional computers cannot. My Science, Technology, and Society (STS) paper examines quantum computing from an institutional level: focusing on research networks and how external pressures can influence the way discoveries are marketed. My technical project examines the low-level material science demands of quantum computing systems: where materials must perform at cryogenic –near absolute zero– temperatures. The technical project focuses on designing a system to measure thermal conductivity at low temperatures. Thermal conductivity describes the rate of heat dissipation in a material and is a key factor controlling the effectiveness of semiconductor performance in a quantum system. However, thermal conductivity is highly temperature dependent, especially near cryogenic temperatures. Further, this property’s behavior varies greatly by material. The goal of the technical project was to accurately and cost-effectively measure thermal conductivity at low temperatures through the three-omega method. To achieve this, we refurbished an existing cryopump to create a precise vacuum and include experimental components. The STS research examines a claim to “quantum supremacy” made by Google in 2019. Using Actor-Network Theory, developed by Micheal Callon and Bruno Latour, I argue that Google’s claim was the outcome of a network of research entities, funding concerns, and reputational actors, that was ultimately destabilized when IBM disproved Google’s central claims. I claim that Google failed to translate its technical success into a sociotechnical claim of “supremacy” because they failed to recruit IBM to the network before their claim. Further, Google inflated the significance of the accomplishment, leading to even greater disappointment when it was disproven. Together, these events led to a total destabilization of the network that had produced Google’s claim to quantum supremacy.

DOI
10.18130/eqk7-a543

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Advanced computing technology is continuously demanding new materials, and the ultra-low temperature regime has become a point of interest in many fields, especially quantum computing. Quantum computing is an emerging field, hoping to leverage quantum mechanics to solve problems that traditional computers cannot. My Science, Technology, and Society (STS) paper examines quantum computing from an institutional level: focusing on research networks and how external pressures can influence the way discoveries are marketed. My technical project examines the low-level material science demands of quantum computing systems: where materials must perform at cryogenic –near absolute zero– temperatures. The technical project focuses on designing a system to measure thermal conductivity at low temperatures. Thermal conductivity describes the rate of heat dissipation in a material and is a key factor controlling the effectiveness of semiconductor performance in a quantum system. However, thermal conductivity is highly temperature dependent, especially near cryogenic temperatures. Further, this property’s behavior varies greatly by material. The goal of the technical project was to accurately and cost-effectively measure thermal conductivity at low temperatures through the three-omega method. To achieve this, we refurbished an existing cryopump to create a precise vacuum and include experimental components. The STS research examines a claim to “quantum supremacy” made by Google in 2019. Using Actor-Network Theory, developed by Micheal Callon and Bruno Latour, I argue that Google’s claim was the outcome of a network of research entities, funding concerns, and reputational actors, that was ultimately destabilized when IBM disproved Google’s central claims. I claim that Google failed to translate its technical success into a sociotechnical claim of “supremacy” because they failed to recruit IBM to the network before their claim. Further, Google inflated the significance of the accomplishment, leading to even greater disappointment when it was disproven. Together, these events led to a total destabilization of the network that had produced Google’s claim to quantum supremacy.
In October 2019, Nature published a paper [6] describing an experimental work that was performed at Google. The paper claims to demonstrate quantum (computational) supremacy on a 53-qubit quantum computer. Since then we have been involved in a long-term project to study various statistical aspects of the Google experiment. In [30] we studied Google's statistical framework that we found to be very sound and offered some technical improvements. This document describes three main concerns (based on statistical analysis) about the Google 2019 experiment. The first concern is that the data do not agree with Google's noise model (or any other specific model). The second concern is that a crucial simple formula for a priori estimation of the fidelity seems to involve an unexpected independence assumption, and yet it gives very accurate predictions. The third concern is about statistical properties of the calibration process.
My 2018 lecture at the ICA workshop in Singapore dealt with quantum computation as a meeting point of the laws of computation and the laws of quantum mechanics. We described a computational complexity argument against the feasibility of quantum computers: we identified a very low-level complexity class of probability distributions described by noisy intermediate-scale quantum computers, and explained why it would allow neither good-quality quantum error-correction nor a demonstration of "quantum supremacy," namely, the ability of quantum computers to make computations that are impossible or extremely hard for classical computers. We went on to describe general predictions arising from the argument and proposed general laws that manifest the failure of quantum computers. In October 2019, "Nature" published a paper describing an experimental work that took place at Google. The paper claims to demonstrate quantum (computational) supremacy on a 53-qubit quantum computer, thus clearly challenging my theory. In this paper, I will explain and discuss my work in the perspective of Google's supremacy claims.
Abstract Quantum computing leverages fundamental quantum-mechanical phenomena—most notably superposition, entanglement, and quantum tunneling—to perform computations in ways that differ fundamentally from classical digital processing. Compared to conventional computing architectures, quantum systems promise significant reductions in computational time and potentially lower energy consumption for specific classes of problems. These advantages, combined with advances in nanoscale engineering and the slowing of traditional hardware scaling trends such as Moore’s Law, have led to substantial commercial and national-security-driven investments in quantum technologies over the past decade. A major milestone was reached when Google announced the experimental demonstration of “quantum supremacy,” showing that a quantum processor could execute a specific computational task infeasible for a classical supercomputer within practical time constraints. Although the demonstrated problem had no immediate practical application, this achievement marked a crucial step toward the development of quantum systems capable of delivering real-world computational advantages and provided a more precise technical framing of the concept of quantum advantage. Despite the fact that the mathematical foundations, programming models, and principal quantum algorithms were established in the 1990s, quantum computing remained largely confined to a specialized research community for decades. Today, the increasing accessibility of cloud-based quantum hardware calls for a broader dissemination of implementation-oriented knowledge among researchers and practitioners in computer science, software engineering, and related fields. The quantum programming paradigm differs fundamentally from classical programming models and often relies on physical and algebraic notations that may pose barriers to traditionally trained computer scientists. This series of articles provides a self-contained and concise introduction to quantum computing and its core algorithms, with a strong emphasis on practical implementation. Given that real quantum processors—such as those accessible via the IBM quantum ecosystem—are now available as cloud services, experimental validation can be conducted both on simulators and on actual hardware for small-scale inputs. While other platforms such as Rigetti and IonQ also offer cloud-based quantum computing services, this review focuses exclusively on the IBM quantum computing ecosystem.
Quantum computing (QC) is often considered a field that has the ability to change a lot of things including how we address certain problems and how we perceive processes. At the same time, it was once said that it would not take long before quantum supremacy is achieved. This is a confrontational point, as several researchers are already stating that some computer problems will never be achievable by quantum computers. Particularly when people think about supremacy, they often tend to refer back to the claims that were made regarding Google's achievement. To dive into this dilemma, different dimensions of QC will need to be specified. There are several directions of interest in QC, which include but are not limited to cryptography, quantum simulation, computer-aided design, and finally quantum key distribution. It is worth noticing that those will not be very helpful in useful satellites or in Global Positioning System (GPS) systems, for instance. However, there are infinitely many satellites sending signals from multiple points into a system and computers trying to pull that off. What is necessary is a somewhat decentralized computer that collects all of this data together and then implements the software required to process this information. Apparently, when and if quantum supremacy is reached, it will allow for solving projects that are today considered impossible or solve them much faster than was ever possible before.
Quantum computation promises to execute certain computational tasks on time scales much faster than any known algorithm on an existing classical computer, for example calculating the prime factors of large integers. Recently a research team from Google claimed to have carried out such a task with a quantum computer, demonstrating in practice a case of this so-called quantum supremacy. Here we argue that this claim was not justified. Unlike other comments, our criticism is concerned with the missing verification of the output data of the quantum computation.
Over the last 20 years there has been a steady increase in fundamental physics research and the hardware development needed to realize a quantum computer. However, in the last 5 years we have seen a dramatic increase in the interest from industry, including a variety of major semiconductor and technology leaders such as IBM, Google and Intel. This is the result of both a better understanding of the variety of problems that can be addressed and the impact that will come with quantum computing along with the emergence of a couple of potentially scalable hardware solutions. In a recent interview with a leading manufacturer, an aggressive strategy was laid out to achieve an operational 1000-qubit quantum computer within 5 years that can solve a variety of problems not addressable by conventional computing and the 10-year prospect to achieve a 1 million qubit machine that would “profoundly change society”. The major technology leaders view quantum information (QI) as a technology that they must begin to develop and understand today. Augmenting existing technology with QI is desirable, but , there are a variety of technical challenges to making silicon-based QI systems with the needed quantum properties and coherence times. New challenges in atomic precision and individual atom or electron effects that fundamentally affect device performance bring on a variety of new manufacturing and metrology challenges. Measuring electron spin coherence, exchange energies, and qubit fidelity are entirely new measurements for the semiconductor industry. Even the resolution of TEM may be inadequate, as TEM of a nominally 80 nm thick slice of silicon which averages many atoms together in a measurement where only one or two atoms can deeply change device performance, coherence times, or introduce charge offsets. After developing some of the first cold atom and ion trap quantum information demonstrations at NIST, we are now investing significantly in developing the supporting metrology and modeling methods needed to help industry develop and commercialize this new technology. In this presentation we will provide an overview of hardware solutions for quantum computing, future metrology needs and challenges to enable manufacturable quantum computers. Although industry leaders are now investing in superconducting qubits and silicon-based qubits, the two leading technologies, this talk will primarily focus on the principles of solid state silicon QI operation, manufacturing metrology solutions, and measurements needed to develop and evaluate viable technological solutions.