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Tuesday, July 21, 2026

Moore's law

From Wikipedia, the free encyclopedia
refer to caption
A semi-log plot of transistor counts for microprocessors against dates of introduction, nearly doubling every two years

Moore's law is the observation that the number of transistors in an integrated circuit (IC) doubles about every two years, with minimal increase in cost. Despite the name, Moore's law describes an empirical relationship, not a scientific law. This type of observation, an experience curve effect, quantifies efficiency gains from learned experience in production.

The observation is named after Gordon Moore, the co-founder of Fairchild Semiconductor and Intel and former Chief Executive Officer of the latter, who in 1965 noted that the number of components per integrated circuit had been doubling every year, and projected that this rate of growth would continue for at least another decade. In 1975, looking forward to the next decade, he revised the forecast to doubling every two years, a compound annual growth rate (CAGR) of 41%. Moore's empirical evidence did not imply that the historical trend would continue; nevertheless, his prediction has held since 1975 and has since become known as a law.

Moore's prediction has been used in the semiconductor industry to guide long-term planning and to set targets for research and development (R&D). Advancements in digital electronics, such as the reduction in quality-adjusted prices of microprocessors, the increase in memory capacity (RAM and flash), the improvement of sensors, and even the number and size of pixels in digital cameras, are strongly linked to Moore's law. These ongoing changes in digital electronics have been a driving force of technological and social change, productivity, and economic growth.

Industry experts have not reached a consensus on exactly when Moore's law will cease to apply. Microprocessor architects report that semiconductor advancement has slowed industry-wide since around 2010, slightly below the pace predicted by Moore's law. In September 2022, Nvidia CEO Jensen Huang considered Moore's law dead, while Intel's then CEO Pat Gelsinger had the opposite view.

History

In 1959, Douglas Engelbart studied the projected downscaling of integrated circuit (IC) size, publishing his results in the article "Microelectronics, and the Art of Similitude". Engelbart presented his findings at the 1960 International Solid-State Circuits Conference, where Moore was present in the audience.

In 1965, Gordon Moore, who at the time was working as the director of research and development at Fairchild Semiconductor, was asked to contribute to the thirty-fifth-anniversary issue of Electronics magazine with a prediction on the future of the semiconductor components industry over the next ten years. His response was a brief article entitled "Cramming more components onto integrated circuits". Within his editorial, he speculated that by 1975 it would be possible to contain as many as 65000 components on a single quarter-square-inch (~ 1.6 cm2) semiconductor.

The complexity for minimum component costs has increased at a rate of roughly a factor of two per year. Certainly over the short term this rate can be expected to continue, if not to increase. Over the longer term, the rate of increase is a bit more uncertain, although there is no reason to believe it will not remain nearly constant for at least 10 years.

Moore posited a log–linear relationship between device complexity (higher circuit density at reduced cost) and time. In a 2015 interview, Moore noted of the 1965 article: "... I just did a wild extrapolation saying it's going to continue to double every year for the next 10 years." One historian of the law cites Stigler's law of eponymy, to introduce the fact that the regular doubling of components was known to many working in the field.

In 1974, Robert H. Dennard at IBM recognized the rapid MOSFET scaling technology and formulated what became known as Dennard scaling, which describes that as MOS transistors get smaller, their power density stays constant such that the power use remains in proportion with area. Evidence from the semiconductor industry shows that this inverse relationship between power density and areal density broke down in the mid-2000s.

At the 1975 IEEE International Electron Devices Meeting, Moore revised his forecast rate, predicting semiconductor complexity would continue to double annually until about 1980, after which it would decrease to a rate of doubling approximately every two years. He outlined several contributing factors for this exponential behavior:

  • The advent of metal–oxide–semiconductor (MOS) technology
  • The exponential rate of increase in die sizes, coupled with a decrease in defective densities, with the result that semiconductor manufacturers could work with larger areas without losing reduction yields
  • Finer minimum dimensions
  • What Moore called "circuit and device cleverness"

Shortly after 1975, Caltech professor Carver Mead popularized the term Moore's law. Moore's law eventually came to be widely accepted as a goal for the semiconductor industry, and it was cited by competitive semiconductor manufacturers as they strove to increase processing power. Moore viewed his eponymous law as surprising and optimistic: "Moore's law is a violation of Murphy's law. Everything gets better and better." The observation was even seen as a self-fulfilling prophecy.

The doubling period is often misquoted as 18 months because of a separate prediction by Moore's colleague, Intel executive David House. In 1975, House noted that Moore's revised law of doubling transistor count every 2 years in turn implied that computer chip performance would roughly double every 18 months, with no increase in power consumption. Mathematically, Moore's law predicted that transistor count would double every 2 years due to shrinking transistor dimensions and other improvements. As a consequence of shrinking dimensions, Dennard scaling predicted that power consumption per unit area would remain constant. Combining these effects, David House deduced that computer chip performance would roughly double every 18 months. Also due to Dennard scaling, this increased performance would not be accompanied by increased power, i.e., the energy-efficiency of silicon-based computer chips roughly doubles every 18 months. Dennard scaling ended in the 2000s. Koomey later showed that a similar rate of efficiency improvement predated silicon chips and Moore's law, for technologies such as vacuum tubes.

Large early portable computer next to a modern smartphone
A 1982 Osborne Executive portable computer, with a 4 MHz 8-bit Zilog Z80 CPU, and a 2007 Apple iPhone with a 412 MHz 32-bit ARM11 CPU; the Executive has 100 times the weight, almost 500 times the volume, approximately 10 times the inflation-adjusted cost, and 1/100th the clock frequency of the smartphone.

Microprocessor architects report that since around 2010, semiconductor advancement has slowed industry-wide below the pace predicted by Moore's law. Brian Krzanich, the former CEO of Intel, cited Moore's 1975 revision as a precedent for the current deceleration, which results from technical challenges and is "a natural part of the history of Moore's law". The rate of improvement in physical dimensions known as Dennard scaling also ended in the mid-2000s. As a result, much of the semiconductor industry has shifted its focus to the needs of major computing applications rather than semiconductor scaling. Nevertheless, as of 2019, leading semiconductor manufacturers TSMC and Samsung Electronics claimed to keep pace with Moore's law with 10, 7, and 5 nm nodes in mass production.

Moore's second law

As the cost of computer power to the consumer falls, the cost for producers to fulfill Moore's law follows an opposite trend: R&D, manufacturing, and test costs have increased steadily with each new generation of chips. The cost of the tools, principally extreme ultraviolet lithography (EUVL), used to manufacture chips doubles every 4 years. Rising manufacturing costs are an important consideration for the sustaining of Moore's law. This led to the formulation of Moore's second law, also called Rock's law (named after Arthur Rock), which is that the capital cost of a semiconductor fabrication plant also increases exponentially over time.

Major enabling factors

A semi-log plot of NAND flash design rule dimensions in nanometers against dates of introduction. The downward linear regression indicates an exponential decrease in feature dimensions over time.
The trend of MOSFET scaling for NAND flash memory allows the doubling of floating-gate MOSFET components manufactured in the same wafer area in less than 18 months.

Numerous innovations by scientists and engineers have sustained Moore's law since the beginning of the IC era. Some of the key innovations are listed below, as examples of breakthroughs that have advanced integrated circuit and semiconductor device fabrication technology, allowing transistor counts to grow by more than seven orders of magnitude in less than five decades.

Computer industry technology road maps predicted in 2001 that Moore's law would continue for several generations of semiconductor chips.

animated plot showing electron density and current as gate voltage varies
A simulation of electron density as gate voltage (Vg) varies in a nanowire MOSFET. The threshold voltage is around 0.45 V. Nanowire MOSFETs lie toward the end of the ITRS road map for scaling devices below 10 nm gate lengths.

One of the key technical challenges of engineering future nanoscale transistors is the design of gates. As device dimensions shrink, controlling the current flow in the thin channel becomes more difficult. Modern nanoscale transistors typically take the form of multi-gate MOSFETs, with the FinFET being the most common nanoscale transistor. The FinFET has gate dielectric on three sides of the channel. In comparison, the gate-all-around MOSFET (GAAFET) structure has even better gate control.

  • A gate-all-around MOSFET (GAAFET) was first demonstrated in 1988, by a Toshiba research team led by Fujio Masuoka, who demonstrated a vertical nanowire GAAFET that he called a surrounding gate transistor (SGT). Masuoka, best known as the inventor of flash memory, later left Toshiba and founded Unisantis Electronics in 2004 to research surrounding-gate technology along with Tohoku University.
  • In 2006, a team of Korean researchers from the Korea Advanced Institute of Science and Technology (KAIST) and the National Nano Fab Center developed a 3 nm transistor, the world's smallest nanoelectronic device at the time, based on FinFET technology.
  • In 2010, researchers at the Tyndall National Institute in Cork, Ireland announced a junctionless transistor. A control gate wrapped around a silicon nanowire can control the passage of electrons without the use of junctions or doping. They claim these may be produced at 10 nm scale using existing fabrication techniques.
  • In 2011, researchers at the University of Pittsburgh announced the development of a single-electron transistor, 1.5 nm in diameter, made out of oxide-based materials. Three wires converge on a central island that can house one or two electrons. Electrons tunnel from one wire to another through the island. Conditions on the third wire result in distinct conductive properties including the ability of the transistor to act as a solid-state memory. Nanowire transistors could spur the creation of microscopic computers.
  • In 2012, a research team at the University of New South Wales announced the development of the first working transistor consisting of a single atom placed precisely in a silicon crystal (not just picked from a large sample of random transistors). Moore's law predicted this milestone to be reached for ICs in the lab by 2020.
  • In 2015, IBM demonstrated 7 nm node chips with silicon–germanium transistors produced using EUVL. The company believed this transistor density would be four times that of the then-current 14 nm chips.
  • Samsung and TSMC plan to manufacture 3 nm GAAFET nodes by 20212022. Note that node names, such as 3 nm, have no relation to the physical size of device elements (transistors).
  • A Toshiba research team including T. Imoto, M. Matsui and C. Takubo developed a system block module wafer bonding process for manufacturing three-dimensional integrated circuit (3D IC) packages in 2001. In April 2007, Toshiba introduced an eight-layer 3D IC, the 16 GB THGAM embedded NAND flash memory chip that was manufactured with eight stacked 2 GB NAND flash chips. In September 2007, Hynix introduced 24-layer 3D IC, a 16 GB flash memory chip that was manufactured with 24 stacked NAND flash chips using a wafer bonding process.
  • V-NAND, also known as 3D NAND, allows flash memory cells to be stacked vertically using charge trap flash technology originally presented by John Szedon in 1967, significantly increasing the number of transistors on a flash memory chip. 3D NAND was first announced by Toshiba in 2007. V-NAND was first commercially manufactured by Samsung Electronics in 2013.
  • In 2008, researchers at HP Labs announced a working memristor, a fourth basic passive circuit element whose existence only had been theorized previously. The memristor's unique properties permit the creation of smaller and better-performing electronic devices.
  • In 2014, bioengineers at Stanford University developed a circuit modeled on the human brain. Sixteen Neurocore chips simulate one million neurons and billions of synaptic connections, claimed to be 9000 times faster as well as more energy efficient than a typical PC.
  • In 2015, Intel and Micron announced 3D XPoint, a non-volatile memory claimed to be significantly faster with similar density compared to NAND. Production scheduled to begin in 2016 was delayed until the second half of 2017.
  • In 2017, Samsung combined its V-NAND technology with eUFS 3D IC stacking to produce a 512 GB flash memory chip, with eight stacked 64-layer V-NAND dies. In 2019, Samsung produced a 1 TB flash chip with eight stacked 96-layer V-NAND dies, along with quad-level cell (QLC) technology (4-bit per transistor), equivalent to 2 trillion transistors, the highest transistor count of any IC chip.
  • In 2020, Samsung Electronics planned to produce the 5 nm node, using FinFET and EUV technology. In 2024, Samsung outlined it's roadmap to include production of a 2 nm chip in 2025.
  • In May 2021, IBM announced the creation of the first 2 nm computer chip, with parts supposedly being smaller than human DNA.

Microprocessor architects report that semiconductor advancement has slowed industry-wide since around 2010, below the pace predicted by Moore's law. Brian Krzanich, the former CEO of Intel, announced in 2015, "Our cadence today is closer to two and a half years than two." Intel stated in 2015 that improvements in MOSFET devices have slowed, starting at the 22 nm feature width around 2012, and continuing at 14 nm. Pat Gelsinger, former Intel CEO, stated at the end of 2023 that "we're no longer in the golden era of Moore's Law, it's much, much harder now, so we're probably doubling effectively closer to every three years now, so we've definitely seen a slowing."

The physical limits to transistor scaling have been reached due to source-to-drain leakage, limited gate metals and limited options for channel material. Other approaches are being investigated, which do not rely on physical scaling. These include the spin state of electron spintronics, tunnel junctions, and advanced confinement of channel materials via nano-wire geometry. Spin-based logic and memory options are being developed actively in labs.

Alternative materials research

The vast majority of current transistors on integrated circuits are composed principally of doped silicon and its alloys. As silicon is fabricated into single nanometer transistors, short-channel effects adversely changes desired material properties of silicon as a functional transistor. Below are several non-silicon substitutes in the fabrication of small nanometer transistors.

One proposed material is indium gallium arsenide, or InGaAs. Compared to their silicon and germanium counterparts, InGaAs transistors are more promising for future high-speed, low-power logic applications. Because of intrinsic characteristics of III–V compound semiconductors, quantum well and tunnel effect transistors based on InGaAs have been proposed as alternatives to more traditional MOSFET designs.

  • In the early 2000s, the atomic layer deposition high-κ film and pitch double-patterning processes were invented by Gurtej Singh Sandhu at Micron Technology, extending Moore's law for planar CMOS technology to 30 nm class and smaller.
  • In 2009, Intel announced the development of 80 nm InGaAs quantum well transistors. Quantum well devices contain a material sandwiched between two layers of material with a wider band gap. Despite being double the size of leading pure silicon transistors at the time, the company reported that they performed equally as well while consuming less power.
  • In 2011, researchers at Intel demonstrated 3-D tri-gate InGaAs transistors with improved leakage characteristics compared to traditional planar designs. The company claims that their design achieved the best electrostatics of any III–V compound semiconductor transistor. At the 2015 International Solid-State Circuits Conference, Intel mentioned the use of III–V compounds based on such an architecture for their 7 nm node.
  • In 2011, researchers at the University of Texas at Austin developed an InGaAs tunneling field-effect transistors capable of higher operating currents than previous designs. The first III–V TFET designs were demonstrated in 2009 by a joint team from Cornell University and Pennsylvania State University.
  • In 2012, a team in MIT's Microsystems Technology Laboratories developed a 22 nm transistor based on InGaAs that, at the time, was the smallest non-silicon transistor ever built. The team used techniques used in silicon device fabrication and aimed for better electrical performance and a reduction to 10 nanometer scale.

Biological computing research shows that biological material has superior information density and energy efficiency compared to silicon-based computing.

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Scanning probe microscopy image of graphene in its hexagonal lattice structure

Various forms of graphene are being studied for graphene electronics, e.g., graphene nanoribbon transistors have shown promise since their appearance in publications in 2008. (Bulk graphene has a band gap of zero and thus cannot be used in transistors because of its constant conductivity, an inability to turn off. The zigzag edges of the nanoribbons introduce localized energy states in the conduction and valence bands and thus a bandgap that enables switching when fabricated as a transistor. As an example, a typical GNR of width of 10 nm has a desirable bandgap energy of 0.4 eV.) More research will need to be performed, however, on sub-50 nm graphene layers, as its resistivity value increases and thus electron mobility decreases.

Forecasts and roadmaps

In April 2005, Gordon Moore stated in an interview that the projection cannot be sustained indefinitely: "It can't continue forever. The nature of exponentials is that you push them out and eventually disaster happens." He also noted that transistors eventually would reach the limits of miniaturization at atomic levels:

In terms of size [of transistors] you can see that we're approaching the size of atoms which is a fundamental barrier, but it'll be two or three generations before we get that far—but that's as far out as we've ever been able to see. We have another 10 to 20 years before we reach a fundamental limit. By then they'll be able to make bigger chips and have transistor budgets in the billions.

Gordon Moore in 2006

In 2016 the International Technology Roadmap for Semiconductors, after using Moore's Law to drive the industry since 1998, produced its final roadmap. It no longer centered its research and development plan on Moore's law. Instead, it outlined what might be called the More than Moore strategy in which the needs of applications drive chip development, rather than a focus on semiconductor scaling. Application drivers range from smartphones to AI to data centers.

IEEE began a road-mapping initiative in 2016, Rebooting Computing, named the International Roadmap for Devices and Systems (IRDS).

Some forecasters, including Gordon Moore, predicted between 2012–2016 that Moore's law would end by around 2025. Although Moore's Law will reach a physical limit, some forecasters in 2019 and 2020 were optimistic about the continuation of technological progress in a variety of other areas, including new chip architectures, quantum computing, and AI and machine learning. Nvidia CEO Jensen Huang declared Moore's law dead in 2022; several days later, Intel CEO Pat Gelsinger countered with the opposite claim.

Consequences

Digital electronics have contributed to world economic growth in the late twentieth and early twenty-first centuries. The primary driving force of economic growth is the growth of productivity, which Moore's law factors into. Moore (1995) expected that "the rate of technological progress is going to be controlled from financial realities". The reverse could and did occur around the late-1990s, however, with economists reporting that "Productivity growth is the key economic indicator of innovation." Moore's law describes a driving force of technological and social change, productivity, and economic growth.

An acceleration in the rate of semiconductor progress contributed to a surge in U.S. productivity growth, which reached 3.4% per year in 1997–2004, outpacing the 1.6% per year during both 1972–1996 and 2005–2013. As economist Richard G. Anderson notes, "Numerous studies have traced the cause of the productivity acceleration to technological innovations in the production of semiconductors that sharply reduced the prices of such components and of the products that contain them (as well as expanding the capabilities of such products)."

The primary negative implication of Moore's law is that it is associated with rapid obsolescence and accordingly high maintenance costs. As technologies continue to rapidly improve, they render predecessor technologies obsolete. In situations in which security and survivability of hardware or data are paramount, or in which resources are limited, rapid obsolescence often poses obstacles to smooth or continued operations.

Intel transistor gate length trend. Transistor scaling

Other formulations and similar observations

Several measures of digital technology are improving at exponential rates related to Moore's law, including the size, cost, density, and speed of components. Moore wrote only about the density of components, "a component being a transistor, resistor, diode or capacitor", at minimum cost.

Transistors per integrated circuit – The most popular formulation is of the doubling of the number of transistors on ICs every two years. At the end of the 1970s, Moore's law became known as the limit for the number of transistors on the most complex chips. The graph at the top of this article shows this trend holds true today. As of 2025, the commercially available processor possessing one of the highest numbers of transistors is a GB202 graphics processor with more than 92.2 billion transistors.

Density at minimum cost per transistor – This is the formulation given in Moore's 1965 paper. It is not just about the density of transistors that can be achieved, but about the density of transistors at which the cost per transistor is the lowest.

As more transistors are put on a chip, the cost to make each transistor decreases, but the chance that the chip will not work due to a defect increases. In 1965, Moore examined the density of transistors at which cost is minimized, and observed that, as transistors were made smaller through advances in photolithography, this number would increase at "a rate of roughly a factor of two per year".

Dennard scaling – This posits that power usage would decrease in proportion to area (both voltage and current being proportional to length) of transistors. Combined with Moore's law, performance per watt would grow at roughly the same rate as transistor density, doubling every 1–2 years. According to Dennard scaling transistor dimensions would be scaled by 30% (0.7×) every technology generation, thus reducing their area by 50%. This would reduce the delay by 30% (0.7×) and therefore increase operating frequency by about 40% (1.4×). Finally, to keep electric field constant, voltage would be reduced by 30%, reducing energy by 65% and power (at 1.4× frequency) by 50%. Therefore, in every technology generation transistor density would double, circuit becomes 40% faster, while power consumption (with twice the number of transistors) stays the same. Dennard scaling ended in 2005–2010, due to leakage currents.

The exponential processor transistor growth predicted by Moore does not always translate into exponentially greater practical CPU performance. Since around 2005–2007, Dennard scaling has ended, so even though Moore's law continued after that, it has not yielded proportional dividends in improved performance. The primary reason cited for the breakdown is that at small sizes, current leakage poses greater challenges, and also causes the chip to heat up, which creates a threat of thermal runaway and therefore, further increases energy costs.

The breakdown of Dennard scaling prompted a greater focus on multicore processors, but the gains offered by switching to more cores are lower than the gains that would be achieved had Dennard scaling continued. In another departure from Dennard scaling, Intel microprocessors adopted a non-planar tri-gate FinFET at 22 nm in 2012 that is faster and consumes less power than a conventional planar transistor. The rate of performance improvement for single-core microprocessors has slowed significantly. Single-core performance was improving by 52% per year in 1986–2003 and 23% per year in 2003–2011, but slowed to just seven percent per year in 2011–2018.

Quality adjusted price of IT equipment – The price of information technology (IT), computers and peripheral equipment, adjusted for quality and inflation, declined 16% per year on average over the five decades from 1959 to 2009. The pace accelerated, however, to 23% per year in 1995–1999 triggered by faster IT innovation, and later, slowed to 2% per year in 2010–2013.

While quality-adjusted microprocessor price improvement continues, the rate of improvement likewise varies, and is not linear on a log scale. Microprocessor price improvement accelerated during the late 1990s, reaching 60% per year (halving every nine months) versus the typical 30% improvement rate (halving every two years) during the years earlier and later. Laptop microprocessors in particular improved 25–35% per year in 2004–2010, and slowed to 15–25% per year in 2010–2013.

The number of transistors per chip cannot explain quality-adjusted microprocessor prices fully. Moore's 1995 paper does not limit Moore's law to strict linearity or to transistor count, "The definition of 'Moore's Law' has come to refer to almost anything related to the semiconductor industry that on a semi-log plot approximates a straight line. I hesitate to review its origins and by doing so restrict its definition."

Hard disk drive areal density – A similar prediction (sometimes called Kryder's law) was made in 2005 for hard disk drive areal density. The prediction was later viewed as over-optimistic. Several decades of rapid progress in areal density slowed around 2010, from 30 to 100% per year to 10–15% per year, because of noise related to smaller grain size of the disk media, thermal stability, and writability using available magnetic fields.

Fiber-optic capacity – The number of bits per second that can be sent down an optical fiber increases exponentially, faster than Moore's law. Keck's law, in honor of Donald Keck.

Network capacity – According to Gerald Butters, the former head of Lucent's Optical Networking Group at Bell Labs, there is another version, called Butters' Law of Photonics, a formulation that deliberately parallels Moore's law. Butters' law says that the amount of data coming out of an optical fiber is doubling every nine months. Thus, the cost of transmitting a bit over an optical network decreases by half every nine months. The availability of wavelength-division multiplexing (sometimes called WDM) increased the capacity that could be placed on a single fiber by as much as a factor of 100. Optical networking and dense wavelength-division multiplexing (DWDM) is rapidly bringing down the cost of networking, and further progress seems assured. As a result, the wholesale price of data traffic collapsed in the dot-com bubble. Nielsen's Law says that the bandwidth available to users increases by 50% annually.

Pixels per dollar – Similarly, Barry Hendy of Kodak Australia has plotted pixels per dollar as a basic measure of value for a digital camera, demonstrating the historical linearity (on a log scale) of this market and the opportunity to predict the future trend of digital camera price, LCD and LED screens, and resolution.

The great Moore's law compensator (TGMLC) – also known as Wirth's law, is the principle that successive generations of computer software increase in size and complexity (software bloat), thereby offsetting the performance gains predicted by Moore's law. In a 2008 article in InfoWorld, Randall C. Kennedy, formerly of Intel, introduces this term using successive versions of Microsoft Office between the year 2000 and 2007 as his premise. Despite the gains in computational performance during this time period according to Moore's law, Office 2007 performed the same task at half the speed on a prototypical year 2007 computer as compared to Office 2000 on a year 2000 computer. Andy and Bill's law is similar.

Library expansion – was calculated in 1945 by Fremont Rider to double in capacity every 16 years, if sufficient space were made available. He advocated replacing bulky, decaying printed works with miniaturized microform analog photographs, which could be duplicated on-demand for library patrons or other institutions. He did not foresee the digital technology that would follow decades later to replace analog microform with digital imaging, storage, and transmission media. Automated, potentially lossless digital technologies allowed vast increases in the rapidity of information growth in an era that now sometimes is called the Information Age.

Carlson curve is a term coined by The Economist to describe the biotechnological equivalent of Moore's law, and is named after author Rob Carlson. Carlson accurately predicted that the doubling time of DNA sequencing technologies (measured by cost and performance) would be at least as fast as Moore's law. Carlson Curves illustrate the rapid (in some cases hyperexponential) decreases in cost, and increases in performance, of a variety of technologies, including DNA sequencing, DNA synthesis, and a range of physical and computational tools used in protein expression and in determining protein structures.

Eroom's law is a pharmaceutical drug development observation that was deliberately written as Moore's Law spelled backward in order to contrast it with the exponential advancements of other forms of technology (such as transistors) over time. It states that the cost of developing a new drug roughly doubles every nine years.

Experience curve effects –says that each doubling of the cumulative production of virtually any product or service is accompanied by an approximate constant percentage reduction in the unit cost. The acknowledged first documented qualitative description of this dates from 1885. A power curve was used to describe this phenomenon in a 1936 discussion of the cost of airplanes.

Edholm's law Phil Edholm, observed that the bandwidth of telecommunication networks (including the Internet) is doubling every 18 months. The bandwidths of online communication networks has risen from bits per second to terabits per second. The rapid rise in online bandwidth is largely due to the same MOSFET scaling that enabled Moore's law, as telecommunications networks are built from MOSFETs.

Haitz's law – predicts that every 10 years, the brightness of LEDs increases 20 fold while the manufacturing cost decreases by a factor of 10.

Swanson's law – is the observation that the price of solar photovoltaic modules tends to drop 20 percent for every doubling of cumulative shipped volume. At present rates, costs go down 75% about every 10 years.

RF Frequency Scaling – In 2025, Asif Alam and Muhmmad Shah Alam proposed an RF analogue to Moore's law based on the historical frontier of transistor maximum oscillation frequency (fmax). Their analysis of reported RF transistors from 1985 to 2025 found that record fmax values increased by approximately 1.6× per decade, with major advances occurring on an approximately 10-year cadence.

Zeno's paradoxes

From Wikipedia, the free encyclopedia

Zeno's paradoxes are a series of philosophical arguments presented by the ancient Greek philosopher Zeno of Elea (c. 490–430 BC), primarily known through the works of Plato, Aristotle, and later commentators like Simplicius of Cilicia. Zeno devised these paradoxes to support his teacher Parmenides's philosophy of monism, which posits that despite people's sensory experiences, reality is singular and unchanging. The paradoxes famously challenge the notions of plurality (the existence of many things), motion, space, and time by suggesting they lead to logical contradictions.

Zeno's work, primarily known from second-hand accounts since his original texts are lost, comprises forty "paradoxes of plurality," which argue against the coherence of believing in multiple existences, and several arguments against motion and change. Of these, only a few are definitively known today, including the renowned "Achilles Paradox", which illustrates the problematic concept of infinite divisibility in space and time. In this paradox, Zeno argues that a swift runner like Achilles cannot overtake a slower moving tortoise with a head start, because the distance between them can be infinitely subdivided, implying Achilles would require an infinite number of steps to catch the tortoise.

These paradoxes have stirred extensive philosophical and mathematical discussion throughout history, particularly regarding the nature of infinity and the continuity of space and time. Initially, Aristotle's interpretation, suggesting a potential rather than actual infinity, was widely accepted. However, modern solutions leveraging the mathematical framework of calculus have provided a different perspective, highlighting Zeno's significant early insight into the complexities of infinity and continuous motion. In the realm of metaphysics, evidence indicates that the "skeptical method" which Zeno adopted to analyze his paradoxes, also influenced the manner in which Immanuel Kant attempted to resolve the paradoxes which were identified within his own antinomies. Zeno's paradoxes remain a pivotal reference point in the philosophical and mathematical exploration of reality, motion, and the infinite, influencing both ancient thought and modern scientific understanding.

History

The origins of the paradoxes are somewhat unclear, but they are generally thought to have been developed to support Parmenides' doctrine of monism, that all of reality is one, and that all change is impossible, that is, that nothing ever changes in location or in any other respect. Diogenes Laërtius, citing Favorinus, says that Zeno's teacher Parmenides was the first to introduce the paradox of Achilles and the tortoise. But in a later passage, Laërtius attributes the origin of the paradox to Zeno, explaining that Favorinus disagrees. Modern academics attribute the paradox to Zeno.

Many of these paradoxes argue that contrary to the evidence of one's senses, motion is nothing but an illusion. In Plato's Parmenides (128a–d), Zeno is characterized as taking on the project of creating these paradoxes because other philosophers claimed paradoxes arise when considering Parmenides' view. Zeno's arguments may then be early examples of a method of proof called reductio ad absurdum, also known as proof by contradiction. Thus Plato has Zeno say the purpose of the paradoxes "is to show that their hypothesis that existences are many, if properly followed up, leads to still more absurd results than the hypothesis that they are one." Plato has Socrates claim that Zeno and Parmenides were essentially arguing exactly the same point. They are also credited as a source of the dialectic method used by Socrates.

Paradoxes

Some of Zeno's nine surviving paradoxes (preserved in Aristotle's Physics and Simplicius's commentary thereon) are essentially equivalent to one another. Aristotle offered a response to some of them. Popular literature often misrepresents Zeno's arguments. For example, Zeno is often said to have argued that the sum of an infinite number of terms must itself be infinite–with the result that not only the time, but also the distance to be travelled, become infinite. However, none of the original ancient sources has Zeno discussing any infinite sum. Simplicius has Zeno saying "it is impossible to traverse an infinite number of things in a finite time". This presents Zeno's problem not with finding the sum, but rather with finishing a task with an infinite number of steps: how can one ever get from A to B, if an infinite number of (non-instantaneous) events can be identified that need to precede the arrival at B, and one cannot reach even the beginning of a "last event"?

Paradoxes of motion

Three of the strongest and most famous—that of Achilles and the tortoise, the Dichotomy argument, and that of an arrow in flight—are presented in detail below.

Dichotomy paradox

The dichotomy

That which is in locomotion must arrive at the half-way stage before it arrives at the goal.

as recounted by Aristotle, Physics VI:9, 239b10

Suppose Atalanta wishes to walk to the end of a path. Before she can get there, she must get halfway there. Before she can get halfway there, she must get a quarter of the way there. Before traveling a quarter, she must travel one-eighth; before an eighth, one-sixteenth; and so on.

The resulting sequence can be represented as:

This description requires one to complete an infinite number of tasks, which Zeno maintains is an impossibility.

This sequence also presents a second problem in that it contains no first distance to run, for any possible (finite) first distance could be divided in half, and hence would not be first after all. Hence, the trip cannot even begin. The paradoxical conclusion then would be that travel over any finite distance can be neither completed nor begun, and so all motion must be an illusion.

This argument is called the "Dichotomy" because it involves repeatedly splitting a distance into two parts. An example with the original sense can be found in an asymptote. It is also known as the Race Course paradox.

Achilles and the tortoise

Achilles and the tortoise

In a race, the quickest runner can never over­take the slowest, since the pursuer must first reach the point whence the pursued started, so that the slower must always hold a lead.

as recounted by Aristotle, Physics VI:9, 239b15

In the paradox of Achilles and the tortoise, Achilles is in a footrace with a tortoise. Achilles allows the tortoise a head start of 100 meters, for example. Suppose that each racer starts running at some constant speed, one faster than the other. After some finite time, Achilles will have run 100 meters, bringing him to the tortoise's starting point. During this time, the tortoise has run a much shorter distance, say 2 meters. It will then take Achilles some further time to run that distance, by which time the tortoise will have advanced farther; and then more time still to reach this third point, while the tortoise moves ahead. Thus, whenever Achilles arrives somewhere the tortoise has been, he still has some distance to go before he can even reach the tortoise. As Aristotle noted, this argument is similar to the Dichotomy. It lacks, however, the apparent conclusion of motionlessness.

Arrow paradox

The arrow

If everything when it occupies an equal space is at rest at that instant of time, and if that which is in locomotion is always occupying such a space at any moment, the flying arrow is therefore motionless at that instant of time and at the next instant of time but if both instants of time are taken as the same instant or continuous instant of time then it is in motion.

as recounted by Aristotle, Physics VI:9, 239b5

In the arrow paradox, Zeno states that for motion to occur, an object must change the position which it occupies. He gives an example of an arrow in flight. He states that at any one (durationless) instant of time, the arrow is neither moving to where it is, nor to where it is not. It cannot move to where it is not, because no time elapses for it to move there; it cannot move to where it is, because it is already there. In other words, at every instant of time there is no motion occurring. If everything is motionless at every instant, and time is entirely composed of instants, then motion is impossible.

Whereas the first two paradoxes divide space, this paradox starts by dividing time—and not into segments, but into points.

Other paradoxes

Aristotle gives three other paradoxes:

Paradox of place

From Aristotle:

If everything that exists has a place, place too will have a place, and so on ad infinitum.

Paradox of the grain of millet

Description of the paradox from the Routledge Dictionary of Philosophy:

The argument is that a single grain of millet makes no sound upon falling, but a thousand grains make a sound. Hence a thousand nothings become something, an absurd conclusion.

Aristotle's response:

Zeno's reasoning is false when he argues that there is no part of the millet that does not make a sound: for there is no reason why any such part should not in any length of time fail to move the air that the whole bushel moves in falling. In fact it does not of itself move even such a quantity of the air as it would move if this part were by itself: for no part even exists otherwise than potentially.

Description from Nick Huggett:

This is a Parmenidean argument that one cannot trust one's sense of hearing. Aristotle's response seems to be that even inaudible sounds can add to an audible sound.

The moving rows (or stadium)

The moving rows

From Aristotle:

... concerning the two rows of bodies, each row being composed of an equal number of bodies of equal size, passing each other on a race-course as they proceed with equal velocity in opposite directions, the one row originally occupying the space between the goal and the middle point of the course and the other that between the middle point and the starting-post. This...involves the conclusion that half a given time is equal to double that time.

An expanded account of Zeno's arguments, as presented by Aristotle, is given in Simplicius's commentary On Aristotle's Physics.

According to Angie Hobbs of The University of Sheffield, this paradox is intended to be considered together with the paradox of Achilles and the Tortoise, problematizing the concept of discrete space & time where the other problematizes the concept of infinitely divisible space & time.

Proposed solutions

In classical antiquity

According to Simplicius, Diogenes the Cynic said nothing upon hearing Zeno's arguments, but stood up and walked, in order to demonstrate the falsity of Zeno's conclusions. To fully solve any of the paradoxes, however, one needs to show what is wrong with the argument, not just the conclusions. Throughout history several solutions have been proposed, among the earliest recorded being those of Aristotle and Archimedes.

Aristotle remarked that as the distance decreases, the time needed to cover those distances also decreases, so that the time needed also becomes increasingly small. Aristotle also distinguished "things infinite in respect of divisibility" (such as a unit of space that can be mentally divided into ever smaller units while remaining spatially the same) from things (or distances) that are infinite in extension ("with respect to their extremities"). Aristotle's objection to the arrow paradox was that "Time is not composed of indivisible nows any more than any other magnitude is composed of indivisibles." Thomas Aquinas, commenting on Aristotle's objection, wrote "Instants are not parts of time, for time is not made up of instants any more than a magnitude is made of points, as we have already proved. Hence it does not follow that a thing is not in motion in a given time, just because it is not in motion in any instant of that time."

In modern mathematics

Some mathematicians and historians, such as Carl Benjamin Boyer, hold that Zeno's paradoxes are simply mathematical problems, for which modern calculus provides a mathematical solution. Infinite processes remained theoretically troublesome in mathematics until the late 19th century. With the definition of limit, Karl Weierstrass and Augustin-Louis Cauchy developed a rigorous formulation of the logic and calculus involved. These works resolved the mathematics involving infinite processes.

Some philosophers, however, say that Zeno's paradoxes and their variations (see Thomson's lamp) remain relevant metaphysical problems. While mathematics can calculate where and when the moving Achilles will overtake the Tortoise of Zeno's paradox, philosophers such as Kevin Brown and Francis Moorcroft hold that mathematics does not address the central point in Zeno's argument, and that solving the mathematical issues does not solve every issue the paradoxes raise. Brown concludes "Given the history of 'final resolutions', from Aristotle onwards, it's probably foolhardy to think we've reached the end. It may be that Zeno's arguments on motion, because of their simplicity and universality, will always serve as a kind of 'Rorschach image' onto which people can project their most fundamental phenomenological concerns (if they have any)."

Henri Bergson

An alternative conclusion, proposed by Henri Bergson in his 1896 book Matter and Memory, is that, while the path is divisible, the motion is not.

Peter Lynds

In 2003, Peter Lynds argued that all of Zeno's motion paradoxes are resolved by the conclusion that instants in time and instantaneous magnitudes do not physically exist. Lynds argues that an object in relative motion cannot have an instantaneous or determined relative position (for if it did, it could not be in motion), and so cannot have its motion fractionally dissected as if it does, as is assumed by the paradoxes. Nick Huggett argues that Zeno is assuming the conclusion when he says that objects that occupy the same space as they do at rest must be at rest.

Bertrand Russell

Based on the work of Georg CantorBertrand Russell offered a solution to the paradoxes, what is known as the "at-at theory of motion". It agrees that there can be no motion "during" a durationless instant, and contends that all that is required for motion is that the arrow be at one point at one time, at another point another time, and at appropriate points between those two points for intervening times. In this view motion is just change in position over time.

Hermann Weyl

Another proposed solution is to question one of the assumptions Zeno used in his paradoxes (particularly the Dichotomy), which is that between any two different points in space (or time), there is always another point. Without this assumption there are only a finite number of distances between two points, hence there is no infinite sequence of movements, and the paradox is resolved. According to Hermann Weyl, the assumption that space is made of finite and discrete units is subject to a further problem, given by the "tile argument" or "distance function problem". According to this, the length of the hypotenuse of a right angled triangle in discretized space is always equal to the sum of the length of the two sides, in contradiction to geometry. Jean Paul Van Bendegem has argued that the Tile Argument can be resolved, and that discretization can therefore remove the paradox.

Applications

Quantum Zeno effect

In 1977, physicists E. C. George Sudarshan and B. Misra discovered that the dynamical evolution (transitions between discrete states) of a quantum system can be inhibited through measurement of the system. This effect is usually called the quantum Zeno effect as it is strongly reminiscent of Zeno's arrow paradox. This effect was first theorized in 1958.

Zeno behaviour

In the field of verification and design of timed and hybrid systems, the system behaviour is called Zeno if it includes an infinite number of discrete steps in a finite amount of time. Some formal verification techniques exclude these behaviours from analysis, if they are not equivalent to non-Zeno behaviour. In systems design these behaviours will also often be excluded from system models, since they cannot be implemented with a digital controller.

Similar paradoxes

School of Names

Diagram of Hui Shi's stick paradox

Roughly contemporaneously during the Warring States period (475–221 BCE), ancient Chinese philosophers from the School of Names, a school of thought similarly concerned with logic and dialectics, developed paradoxes similar to those of Zeno. The works of the School of Names have largely been lost, with the exception of portions of the Gongsun Longzi. The second of the Ten Theses of Hui Shi suggests knowledge of infinitesimals:That which has no thickness cannot be piled up; yet it is a thousand li in dimension. Among the many puzzles of his recorded in the Zhuangzi is one very similar to Zeno's Dichotomy:

"If from a stick a foot long you every day take the half of it, in a myriad ages it will not be exhausted."

Zhuangzi, chapter 33 (Legge translation)

The Mohist canon appears to propose a solution to this paradox by arguing that in moving across a measured length, the distance is not covered in successive fractions of the length, but in one stage. Due to the lack of surviving works from the School of Names, most of the other paradoxes listed are difficult to interpret.

"What the Tortoise Said to Achilles", written in 1895 by Lewis Carroll, describes a paradoxical infinite regress argument in the realm of pure logic. It uses Achilles and the Tortoise as characters in a clear reference to Zeno's paradox of Achilles.

Renormalization

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Renormalization Renormalization i...