The semiconductor landscape has historically been a testament to human ingenuity, rapidly evolving from bulky 20th-century transistors to today's nanoscale wonders. These incredible feats of engineering have continually reshaped the electronics domain, enabling devices to become smaller, faster and more energy efficient.
Alongside breakthroughs in materials and inventive applications, the industry now stands on the precipice of another revolutionary phase. Quantum computing (QC), albeit still nascent, emerges as the latest groundbreaking challenge. It promises, and is widely expected, to usher in transformative shifts, particularly in semiconductor design, manufacturing and pioneering applications.
Setting the quantum stage
To understand QC, there is a fundamental and foundational difference from classical computing. Traditional systems store and process data in binary form, strictly interpreting each bit as either a 0 or a 1. QC diverges radically from this model, introducing the concept of qubits. Unlike binary bits, qubits have the unique ability to exist in a superposition of both 0 and 1 states simultaneously, thanks to the principles of quantum mechanics that they leverage. Such a paradigm, known as quantum parallelism, amplifies computational power. It enables quantum computers to theoretically perform millions of operations using multifaceted data processing in parallel, capabilities that classical computers cannot match.
This heightened computational ability of QC opens doors to numerous applications. QC has the potential to handle a wide range of tasks including financial risk calculations, molecular science, intelligent traffic management, vaccine discovery and weather forecasting. Moreover, it is primed to synergize with technologies like 5G, artificial intelligence (AI) and the internet of things (IoT).
Foundational algorithms and proposals: The birth of QC
The concept of QC can be traced back to the 1980s when its potential was first posited to enhance the computational modeling of minuscule quantum systems. A surge of enthusiasm enveloped the scientific community in the 1990s and groundbreaking algorithms and proposals were introduced.
While Shor's algorithm caught the limelight for its promise to significantly expedite specific cryptanalysis and challenge cryptographic systems that protect global communication and data storage, it wasn't alone. Grover's algorithm, another seminal proposal, hinted at a quantum solution for database searching at a speed unattainable by classical counterparts. These innovative algorithms symbolized the vast potential of QC and ignited widespread interest within the scientific community.
Transitioning from foundations to functionality
By 2017, the QC narrative began shifting from theoretical foundations to tangible manifestations. The appearance of Noisy Intermediate-Scale Quantum (NISQ) computers heralded this change. These machines, equipped with tens of qubits, represented significant progress.
Yet, they had their limitations. They had error rates too high to correct. Running parallel to these developments was the realm of quantum annealing. Originating a decade earlier, this approach harnessed qubits with reduced coherence durations but demonstrated impressive scalability, achieving experimental quantum annealers with approximately 2,000 qubits.
QC today: A glimpse into the present
As we transition to the present, the QC timeline is accelerating. In recent years, milestones have been achieved at a remarkable pace, with industry stalwarts expressing confidence in the commercial viability of QC. While full-scale commercial applications may still be a few years away, the trajectory of progress is undeniable.
Quantum computing may hold new ways to develop semiconductors only previously imagined in works of science fiction. Source: Vegefox.com/AdobeStock
Navigating quantum quandaries
While the promise of QC is exciting, transitioning from the lab to broad application has its challenges.
Inherent sensitivity to noise in qubits
Nature of the challenge: In classical computing, the binary system effectively filters out minor noise discrepancies. However, QC faces heightened vulnerability data corruption due to a qubit's potential simultaneous representation of both 0 and 1.
Real-world impact: In applications like drug discovery or climate modeling, a slight noise-induced error can lead to incorrect molecular structures or skewed climate predictions.
Quantum error correction (QEC)
Nature of the challenge: Qubits are inherently error-prone, which makes QEC indispensable. QEC is fundamentally different from classical error correction, primarily due to the probabilistic nature of qubits.
Real-world impact: QEC algorithms aim to emulate noise-free quantum computers but impose significant overhead. Many physical qubits might be needed to construct a single, stable logical qubit. This multiplies the complexity and resources required, meaning early quantum computers might not be error-free.
Decoherence
Nature of the challenge: The fleeting stability of qubits, or decoherence, refers to their tendency to lose quantum behavior quickly. This quality poses a monumental challenge because qubits that lose coherence fail to act quantumly.
Real-world impact: Decoherence disrupts error correction, system optimization, and scaling efforts. In practical terms, a quantum computer that handles financial simulations could potentially yield incorrect risk assessments.
Data processing and debugging
Nature of the challenge: Quantum computers can represent vast data using fewer qubits, but converting classical data into a quantum state is resource intensive. Additionally, quantum algorithms rely on unique phenomena such as interference and entanglement.
Real-world impact: As we envision real-world applications like logistics optimization or AI enhancement, the time spent on data conversion could negate the quantum speed advantage. Moreover, the absence of a mature quantum software stack and the infeasibility of traditional debugging methods may impede the development and deployment of quantum algorithms.
The quantum dawn
Despite challenges, the anticipation surrounding QC’s transformative power is undeniable with "quantum supremacy" being a coveted milestone. This is characterized by a quantum computer's capacity to perform tasks unimaginable for classical counterparts.
Significantly, researchers at Google have made strides that could be important to overcoming some of the challenges. They recently announced a system with 70 operational qubits functioning at 24 cycles. Using a complex, synthetic benchmark of random circuit sampling, they have optimized the speed of critical operations, possibly addressing the previously mentioned sensitivity to external noise. To underscore the magnitude of this breakthrough, it would take 47 years for a current supercomputer to crunch the same numbers that Google’s quantum system is reported to have tackled.
This rapid progression is supported by the financial world’s increasing confidence in QC. Funding of start-ups focused on quantum technologies more than doubled to $1.4 billion in 2021 from the year before. Furthermore, McKinsey & Co. has projected that the QC market could reach $700 billion by 2035, potentially surpassing $90 billion annually by 2040.
Conclusion
QC and semiconductor development share a symbiotic relationship. The future is teeming with potential. Imagine a world where drug discovery moves faster and artificial intelligence surpasses current capabilities, offering a glimpse into the revolution ahead. Yet, this envisioned future is punctuated by significant technical hurdles, the most pressing being the quest for durable, error-correcting qubits in unprecedented quantities.
As the quantum realm approaches supremacy, it is the semiconductor industry that stands at a transformative crossroads. It is not a mere spectator or facilitator, but rather the agent for sculpting the very future of QC. The advancements in QC will invariably catalyze innovations in semiconductor technology, and vice versa. The message to all stakeholders, from manufacturers to researchers, is clear: prepare for a quantum revolution that will reshape both computation and semiconductor innovation.
Supplemental reading
These sources provide information on QC and its role in the semiconductor space.
- Anonymous; Sanjaya. (2023, July 9). Exploring the future of quantum computing: What you need to know.
- National Academies of Sciences. (2018, December 4). Quantum Computing: Progress and Prospects | The National Academies Press.
- Larsen, K. (2021, November 8). What is quantum computing? Applications & Challenges | Synopsys Blog.
About the author
Emily Main holds a J.D. in Compliance Law and a B.S. in Telecommunications. With her rich expertise in semiconductor technology and digital networking, she is well-positioned at the crossroads of technology, policy and sustainability. Main has made extensive contributions to a wide array of publications, exploring technical challenges, industry trends and their implications.
