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Spices at a central market in Agadir, Morocco
A group of Indian herbs and spices in bowls
Spices of Saúde flea market, São Paulo, Brazil

In the culinary arts, a spice is any seed, fruit, root, bark, or other plant substance in a form primarily used for flavoring or coloring food. Spices are distinguished from herbs, which are the leaves, flowers, or stems of plants used for flavoring or as a garnish. Spices and seasoning do not mean the same thing, but spices fall under the seasoning category with herbs. Spices are sometimes used in medicine, religious rituals, cosmetics, or perfume production. They are usually classified into spices, spice seeds, and herbal categories.[1] For example, vanilla is commonly used as an ingredient in fragrance manufacturing.[2] Plant-based sweeteners such as sugar are not considered spices.

Spices can be used in various forms, including fresh, whole, dried, grated, chopped, crushed, ground, or extracted into a tincture. These processes may occur before the spice is sold, during meal preparation in the kitchen, or even at the table when serving a dish, such as grinding peppercorns as a condiment. Certain spices, like turmeric[dubious – discuss], are rarely available fresh or whole and are typically purchased in ground form. Small seeds, such as fennel and mustard, can be used either in their whole form or as a powder, depending on the culinary need.

A whole dried spice has the longest shelf life, so it can be purchased and stored in larger amounts, making it cheaper on a per-serving basis. A fresh spice, such as ginger, is usually more flavorful than its dried form, but fresh spices are more expensive and have a much shorter shelf life.

There is not enough clinical evidence to indicate that consuming spices affects human health.[3]

India contributes to 75% of global spice production.[4] This is reflected culturally through its cuisine. Historically, the spice trade developed throughout the Indian subcontinent as well as in East Asia and the Middle East. Europe's demand for spices was among the economic and cultural factors that encouraged exploration in the early modern period.

Definition

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Although defining spice is difficult, varying definitions cover several common aspects. One such aspect is the biological source of spices: the Oxford English Dictionary (OED) identifies the source as vegetables, while Redgrove (1933) is more specific as to the part of the plant, specifically the root, rhizome, flower, fruit, seed and bark when they are dried, in contrast with herbaceous parts which constitute herbs. The Oxford Companion to Food challenges spices as sourced from plants being a hard rule, pointing to ambergris being often identified as a spice despite its animal origin.[5]

Another aspect is the geographical source: The OED specifies spices are sourced from the tropics, while The Oxford Companion to Food gives the example of caraway seeds as demonstrating that spices can come from temperate climes. The notion that spices have a tropical origin is historic: originally "spice" was understood as a type of merchandise from the Orient. As Europeans encountered the Americas, beginning the Columbian exchange, the meaning expanded to capture new aromatics, and the meaning later shifted again to refer to culinary use. This historic development has led to some ingredients indigenous to European cooking such as garlic and horseradish not being considered spices despite sharing many attributes.[5]

History

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See also: Spice use in antiquity

Early history

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Archeological study of early spice use is difficult, as spices were used in small quantities, leaving few preserved remains.[6]

The spice trade developed throughout the Indian subcontinent[7] and Middle East by 2000 BCE with cinnamon and black pepper, and in East Asia with herbs and pepper. The Egyptians used herbs for cuisine and mummification. Their demand for exotic spices and herbs helped stimulate world trade.

Cloves were used in Mesopotamia by 1700 BCE.[note 1] The earliest written records of spices come from ancient Egyptian, Chinese, and Indian cultures. The Ebers Papyrus from early Egypt dating from 1550 BCE describes some eight hundred different herbal medicinal remedies and numerous medicinal procedures.[11]

By 1000 BCE, medical systems based on herbs could be found in China, Korea, and India.[12] Early uses were associated with magic, medicine, religion, tradition, and preservation.[13]

Indonesian merchants traveled around China, India, the Middle East, and the east coast of Africa. Arab merchants facilitated the routes through the Middle East and India. This resulted in the Egyptian port city of Alexandria being the main trading center for spices. The most important discovery prior to the European spice trade was the monsoon winds (40 CE). Sailing from Eastern spice cultivators to Western European consumers gradually replaced the land-locked spice routes once facilitated by the Middle East Arab caravans.[13]

Spices were prominent enough in the ancient world that they are mentioned in the Old Testament. In Genesis, Joseph was sold into slavery by his brothers to spice merchants. In Exodus, manna is described as being similar to coriander in appearance. In the Song of Solomon, the male narrator compares his beloved to many saffron, cinnamon, and other spices.[14]

Historians believe that nutmeg, which originates from the Banda Islands in Southeast Asia, was introduced to Europe in the 6th century BCE.[15] The Romans had cloves in the 1st century CE, as Pliny the Elder wrote about them.[16]

Middle Ages

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"The Mullus" harvesting pepper. Illustration from a French edition of The Travels of Marco Polo.

Spices were among the most demanded and expensive products available in Europe in the Middle Ages,[5] the most common being black pepper, cinnamon (and the cheaper alternative cassia), cumin, nutmeg, ginger, and cloves. Given medieval medicine's main theory of humorism, spices and herbs were indispensable to balance "humors" in food,[6] on a daily basis for good health at a time of recurrent pandemics. In addition to being desired by those using medieval medicine, the European elite also craved spices in the Middle Ages, believing spices to be from and a connection to "paradise".[17] An example of the European aristocracy's demand for spice comes from the King of Aragon, who invested substantial resources into importing spices to Spain in the 12th century. He was specifically looking for spices to put in wine and was not alone among European monarchs at the time to have such a desire for spice.[18]

Spices were all imported from plantations in Asia and Africa, which made them expensive. From the 8th until the 15th century, the Republic of Venice held a monopoly on spice trade with the Middle East, using this position to dominate the neighboring Italian maritime republics and city-states. The trade made the region rich. It has been estimated that around 1,000 tons of pepper and 1,000 tons of other common spices were imported into Western Europe each year during the Late Middle Ages. The value of these goods was the equivalent of a yearly supply of grain for 1.5 million people.[19] The most exclusive was saffron, used as much for its vivid yellow-red color as for its flavor. Spices that have now fallen into obscurity in European cuisine include grains of paradise, a relative of cardamom which mostly replaced pepper in late medieval north French cooking, along with long pepper, mace, spikenard, galangal, and cubeb.[20]

Early modern period

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Voyagers from Spain and Portugal were interested in seeking new routes to trade in spices and other valuable products from Asia. The control of trade routes and the spice-producing regions were the main reasons that Portuguese navigator Vasco da Gama sailed to India in 1499.[8] When da Gama discovered the pepper market in India, he was able to secure peppers for a much lower cost than demanded by Venice.[18] At around the same time, Christopher Columbus returned from the New World. He described to investors the new spices available there.[21][a]

Another source of competition in the spice trade during the 15th and 16th centuries was the Ragusans from the maritime republic of Dubrovnik in southern Croatia.[22] The military prowess of Afonso de Albuquerque (1453–1515) allowed the Portuguese to take control of the sea routes to India. In 1506, he took the island of Socotra in the mouth of the Red Sea and, in 1507, Ormuz in the Persian Gulf. Since becoming the viceroy of the Indies, he took Goa in India in 1510, and Malacca on the Malay Peninsula in 1511. The Portuguese could now trade directly with Siam, China, and the Maluku Islands.[citation needed]

With the discovery of the New World came new spices, including allspice, chili peppers, vanilla, and chocolate. This development kept the spice trade, with the Americas as a latecomer with their new seasonings, profitable well into the 19th century.[23]

Function

[edit]
Chili powder, mustard seeds, turmeric powder, cumin seeds
Turmeric powder, mustard seeds, chilli powder, cumin seeds

Spices are primarily used as food flavoring or to create variety.[24] They are also used to perfume cosmetics and incense. At various periods, many spices were used in herbal medicine. Finally, since they can be expensive, rare and exotic commodities, their conspicuous consumption has often been a symbol of wealth and social class.[20]

Preservative claim

[edit]

The most popular explanation for the love of spices in the Middle Ages is that they were used to preserve meat from spoiling, or to cover up the taste of meat that had already gone off. This compelling but false idea constitutes something of an urban legend, a story so instinctively attractive that mere fact seems unable to wipe it out... Anyone who could afford spices could easily find meat fresher than what city dwellers today buy in their local supermarket.[20]

It is often claimed that spices were used either as food preservatives or to mask the taste of spoiled meat, especially in the European Middle Ages.[20][25] This is false.[26][27][28][20] In fact, spices are rather ineffective as preservatives as compared to salting, smoking, pickling, or drying, and are ineffective in covering the taste of spoiled meat.[20] Moreover, spices have always been comparatively expensive: in 15th century Oxford, a whole pig cost about the same as a pound of the cheapest spice, pepper.[20] There is also no evidence of such use from contemporary cookbooks: "Old cookbooks make it clear that spices weren't used as a preservative. They typically suggest adding spices toward the end of the cooking process, where they could have no preservative effect whatsoever."[29] Indeed, Cristoforo di Messisbugo suggested in the 16th century that pepper may speed up spoilage.[29]

Though some spices have antimicrobial properties in vitro,[30] pepper—by far the most common spice—is relatively ineffective, and in any case, salt, which is far cheaper, is also far more effective.[29]

Classification and types

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See also: Outline of herbs and spices
A plate of Indian herbs and spices

Culinary herbs and spices

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Main article: List of culinary herbs and spices

Botanical basis

[edit]

Common spice mixtures

[edit]
Main article: Spice mix

Handling

[edit]
A shelf of common spices for a home kitchen in Canada or the United States

Pepper mill

A mortar and pestle is the classic set of tools for grinding a whole spice. Less labor-intensive tools are more common now: a microplane or fine grater can be used to grind small amounts; a coffee grinder[note 2] is useful for larger amounts. A frequently used spice such as black pepper may merit storage in its own hand grinder or mill.

The flavor of a spice is derived in part from compounds (volatile oils) that oxidize or evaporate when exposed to air. Grinding a spice greatly increases its surface area and so increases the rates of oxidation and evaporation. Thus, the flavor is maximized by storing a spice whole and grinding when needed. The shelf life of a whole dry spice is roughly two years; of a ground spice roughly six months.[31] The "flavor life" of a ground spice can be much shorter.[note 3] Ground spices are better stored away from light.[note 4]

Some flavor elements in spices are soluble in water; many are soluble in oil or fat. As a general rule, the flavors from a spice take time to infuse into the food so spices are added early in preparation. This contrasts to herbs which are usually added late in preparation.[31]

Salmonella contamination

[edit]

A study by the Food and Drug Administration of shipments of spices to the United States during fiscal years 2007–2009 showed about 7% of the shipments were contaminated by Salmonella bacteria, some of it antibiotic-resistant.[32] As most spices are cooked before being served salmonella contamination often has no effect, but some spices, particularly pepper, are often eaten raw and are present at the table for convenient use. Shipments from Mexico and India, a major producer, were the most frequently contaminated.[33] Food irradiation is said to minimize this risk.[34][35]

Production

[edit]
Spices and herbs at a shop in Goa, India
Top Spice Producing Countries
(in metric tonnes)
Rank Country 2010 2011
1 India 1,474,900 1,525,000
2 Bangladesh 128,517 139,775
3 Turkey 107,000 113,783
4 China 90,000 95,890
5 Pakistan 53,647 53,620
6 Iran 18,028 21,307
7 Nepal 20,360 20,905
8 Colombia 16,998 19,378
9 Ethiopia 27,122 17,905
10 Sri Lanka 8,293 8,438
— World 1,995,523 2,063,472
Source: UN Food & Agriculture Organization[36]

Standardization

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The International Organization for Standardization addresses spices and condiments, along with related food additives, as part of the International Classification for Standards 67.220 series.[37]

[edit]
  • The Gato Negro café and spice shop (Buenos Aires, Argentina)
    The Gato Negro café and spice shop (Buenos Aires, Argentina)
  • A spice shop selling a variety of spices in Iran
    A spice shop selling a variety of spices in Iran
  • Night spice shop in Casablanca, Morocco
    Night spice shop in Casablanca, Morocco
  • A spice shop in Taliparamba, India
    A spice shop in Taliparamba, India
  • Spices sold in Taliparamba, India
    Spices sold in Taliparamba, India
  • Spice seller at a market in Kashgar, China
    Spice seller at a market in Kashgar, China
  • Spice market, Marrakesh, Morocco
    Spice market, Marrakesh, Morocco

See also

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Notes

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References

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Sources

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Further reading

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Spice

View on Grokipedia
from Grokipedia
SPICE (Simulation Program with Integrated Circuit Emphasis) is a general-purpose, open-source analog simulator used by engineers to mathematically predict the behavior of in and board-level designs. It performs nonlinear DC, nonlinear transient, and linear AC analyses on circuits comprising passive components like resistors, capacitors, and inductors, as well as active elements such as diodes, bipolar junction transistors (BJTs), and metal-oxide-semiconductor field-effect transistors (MOSFETs). Originally developed at the , SPICE has evolved into the foundational tool for verifying circuit integrity and optimizing performance prior to physical fabrication. The origins of SPICE trace back to 1970, when it was created as a graduate student class project in the Department of and Computer Sciences (EECS) at UC Berkeley, under the of O. Pederson. Laurence W. Nagel, a PhD candidate at the time, led the development, building on earlier Berkeley simulators like CANCER (Circuit Analysis with Network Extended Routines), which had been initiated by Professor Ronald A. Rohrer in 1968. The first version, SPICE1, incorporated advanced techniques such as methods for efficient computation and built-in models for devices, making it accessible for academic and early industrial use. Released into the in 1972, its open-source nature allowed widespread adoption and spurred continuous enhancements by academia and industry. Over the decades, SPICE has influenced the electronics industry profoundly, becoming the de facto standard for analog and mixed-signal circuit simulation and enabling the design of increasingly complex integrated circuits. Its availability as open-source code facilitated the creation of numerous compatible implementations, including commercial variants like HSPICE from Synopsys for high-precision simulations and LTspice from Analog Devices, which offers schematic capture and waveform viewing enhancements. Open-source derivatives such as ngspice provide robust support for mixed analog-digital circuits and integration with tools like KiCad. These variants maintain compatibility with SPICE's netlist format while adding features like behavioral modeling and faster solvers for large-scale designs. By the 1980s, SPICE had trained hundreds of engineers and contributed to U.S. leadership in microelectronics, remaining essential for modern semiconductor innovation despite advancements in digital and RF simulation tools.

History

Origins and Development

The development of SPICE began in the late at the , driven by the need to simulate increasingly complex integrated circuits as transistor counts grew rapidly in design. In 1968, faculty member Ronald A. Rohrer introduced a course on computer analysis of nonlinear circuits, which laid the groundwork for advanced simulation tools to address the limitations of manual analysis and early linear approximation methods. Donald O. Pederson, a professor in the Department of and Computer Sciences, oversaw the project as thesis advisor, with graduate student Laurence W. Nagel leading the implementation efforts after Rohrer's departure from Berkeley. The original name, Simulation Program with Integrated Circuit Emphasis (SPICE), reflected its focus on modeling integrated circuits, particularly emphasizing nonlinear device behaviors that earlier tools could not accurately capture. Key motivations included the demand for precise nonlinear DC, transient, and small-signal analyses to go beyond the linear approximations employed in predecessors like IBM's ECAP and ECAP-II, which were insufficient for the nonlinear characteristics of diodes and transistors in modern ICs. The program built on foundational physics, incorporating equations and early transistor models such as the Ebers-Moll equations for bipolar junction transistors. Early funding came from the (NSF), supporting the academic research environment at Berkeley that enabled this innovation. The project evolved from an initial program called CANCER (Computer Analysis of Nonlinear Circuits, Excluding Radiation), building on even earlier Berkeley tools like , SLIC, and TIME, and developed as a class project and publicly described in a 1971 paper by Nagel and Rohrer. This precursor was released for limited use in 1971, with the first version of SPICE (SPICE1) released to limited users in fall 1971 and publicly introduced in April 1973, marking a significant milestone in accessible circuit simulation. By 1973, Nagel and Pederson formalized SPICE in a , establishing it as a robust tool for .

Initial Implementations and Milestones

The initial implementation of SPICE, known as SPICE1, was publicly released in 1973 by Laurence W. Nagel and Donald O. Pederson at the . Written in , it emphasized simulation of integrated circuits through and supported DC operating point analysis, transient analysis, and small-signal AC analysis, with models for both MOS and bipolar transistors. This version was designed to handle circuits up to 50 nodes and 25 bipolar transistors, using a fixed timestep for transient simulations on mainframe computers like the CDC 6400. SPICE2, released in 1975 as part of Nagel's PhD dissertation and further developed until 1977 under the leadership of Pederson and contributions from researchers like A. Richard Newton and , introduced significant enhancements to address limitations in SPICE1. Key improvements included better convergence algorithms for nonlinear solvers, the addition of to evaluate circuit parameter variations, and support for via subcircuit definitions, enabling hierarchical circuit representation. These features expanded its utility for more complex MOS and bipolar designs, while maintaining with SPICE1 input formats. A pivotal milestone came with the release of SPICE2G.6 in 1983, which solidified its role as a semi-official standard for circuit simulation due to refined and broader device modeling. This version saw rapid adoption in universities for educational purposes and in industry for verification, forming the foundation for many commercial simulators. By 1980, Berkeley had distributed thousands of copies, influencing parallel developments such as IBM's ASTAP simulator, which adopted similar techniques but emphasized sparse tableau formulations for larger circuits. SPICE implementations tackled key technical challenges in simulating stiff differential equations arising from circuit dynamics, particularly in transient analysis. SPICE2 incorporated Gear's method, a stiffly stable that improved integration accuracy and convergence for systems with widely varying time constants, outperforming explicit methods in handling nonlinear device behaviors. From its inception, SPICE benefited from UC Berkeley's policy of releasing the software into the without licensing fees, encouraging widespread academic and industrial use and fostering an ecosystem of modifications and extensions. This open approach, championed by Pederson, ensured free distribution and modification rights, accelerating its integration into global engineering workflows.

Successors and Implementations

Open-Source Variants

, initiated in 1993 as a of the Berkeley SPICE 3f.5 release, serves as a prominent open-source mixed-signal circuit simulator that incorporates extensions from the Cider1b1 and Xspice packages for enhanced device modeling and digital simulation capabilities. It supports a wide range of analyses, including transient, , and noise simulations, while enabling mixed analog-digital workflows through XSPICE code models for behavioral extensions. Active development continues, with the latest stable release, version 45.2, issued on September 6, 2025, featuring bug fixes and improved compatibility for Windows environments. Additionally, provides Python bindings via its shared library interface, allowing seamless integration into Python-based workflows for automated simulations and data analysis through libraries like PySpice. Developed by starting in the early 2000s, Xyce is a SPICE-compatible simulator optimized for parallel processing on clusters, enabling efficient handling of large-scale circuits with millions of devices. Its architecture leverages distributed-memory parallelism to reduce simulation times for complex analog and mixed-signal designs, supporting standard SPICE netlists alongside advanced analyses like and sensitivity. First released as under the GNU General Public License in 2013, Xyce remains actively maintained by Sandia, with ongoing enhancements for scalability in scientific and engineering applications. Qucs-S, a variant of the original (Qucs) project from the early , integrates open-source SPICE engines such as and Xyce within a unified for and simulation. Launched in its stable form around 2017, it emphasizes RF and system-level simulations, including modeling, analysis, and ESD effects, while maintaining compatibility with SPICE netlists for hybrid workflows. The tool's backend-agnostic design allows users to select simulation kernels dynamically, facilitating advanced features like model support when paired with compatible engines. Post-2020 developments in these variants have focused on extensibility, with introducing Verilog-A support through the OSDI/OpenVAF interface starting in version 39 (2022), enabling compact device models for more accurate behavioral simulations via community-contributed compilers. Community efforts have also explored integration with for model optimization, such as using neural networks to accelerate transient analysis and genetic algorithms for analog circuit sizing, as detailed in recent research frameworks. These advancements, driven by open contributions on platforms like , enhance the tools' adaptability for modern design challenges. All major open-source SPICE variants—ngspice under the modified BSD license, Xyce under the GNU GPL, and Qucs-S under GPL-2.0—promote accessibility for academic, research, and hobbyist use by allowing free distribution, modification, and integration without proprietary restrictions. This licensing model fosters widespread adoption and collaborative improvement, distinguishing them from commercial tools while enabling extensions for specialized applications.

Commercial Derivatives

Commercial derivatives of SPICE have evolved into proprietary simulators tailored for professional (EDA) workflows, offering enhanced performance, integration with , and specialized analyses for industry applications. These tools, developed by major EDA vendors, provide optimized algorithms, advanced device models, and user interfaces that support complex circuit verification in and PCB design, often under licensing models that ensure reliability and support for enterprise users. LTspice, introduced by Linear Technology in the late 1990s and maintained by Analog Devices following the 2017 acquisition, is a freeware SPICE simulator featuring an integrated schematic editor for circuit capture and a waveform viewer for results analysis. It includes fast Monte Carlo analysis capabilities to evaluate component tolerances and variations, making it a staple for analog circuit design and prototyping among engineers. Recent updates, such as those in LTspice 24 released in 2024 with further model enhancements in late 2025, have improved simulation speed and consistency while supporting behavioral modeling sources for arbitrary voltage and current expressions. PSpice, originating in the 1980s from MicroSim and now part of Cadence's suite since 1999, excels in analog and mixed-signal simulation with advanced waveform viewing tools for detailed signal inspection and support for hierarchical design entry to manage large schematics efficiently. It integrates seamlessly with PCB layout environments like PCB Designer and Allegro, enabling simulation-driven optimization from schematic to board-level verification. These features facilitate rapid iteration in and analysis. Spectre, developed by starting in the late , is a high-performance circuit simulator optimized for analog, RF, and mixed-signal () designs, with extensions like SpectreRF for radio-frequency analysis and Spectre AMS Designer for system-level verification. It natively supports for behavioral modeling of mixed-signal systems, allowing co-simulation of analog and digital blocks in complex SoCs. Widely adopted in and AMS SoC verification, it delivers scalable parallel processing for large-scale designs. HSPICE from emphasizes precision in simulating nanometer-scale circuits, leveraging foundry-qualified models for accurate characterization of transistors and interconnects at advanced process nodes like 45 nm and below. It includes robust statistical variation analysis through and variability tools to assess process-induced mismatches and yield impacts in high-volume . This makes it essential for custom IC design where timing and power accuracy are critical. These commercial SPICE derivatives dominate the EDA landscape, with and holding significant market shares in tools amid a global EDA market projected to reach USD 19.22 billion in 2025. Licensing models typically involve annual fees scaled to usage and support levels, supporting their role in professional workflows. Recent trends include cloud-based integrations, such as AWS-compatible deployments for scalable by 2023, contrasting with open-source variants that prioritize over enterprise optimization.

Technical Architecture

Simulation Analyses

SPICE employs modified to formulate circuit equations based on Kirchhoff's laws and device characteristics, enabling the solution of large systems through techniques. This foundation supports multiple types, each addressing specific aspects of circuit performance, such as steady-state operation, time-domain responses, and frequency-domain behaviors. The core solver uses iterative numerical methods to handle nonlinearity, with convergence ensured through specialized techniques. These analyses assume prior definition of device models, which provide the nonlinear relationships between voltages, currents, and charges. DC analysis in SPICE determines the steady-state of a circuit by solving a system of nonlinear algebraic derived from the nodal formulation. The primary is G⋅V=I\mathbf{G} \cdot \mathbf{V} = \mathbf{I}, where G\mathbf{G} is the conductance matrix incorporating nonlinear device conductances, V\mathbf{V} is the vector of node voltages, and I\mathbf{I} is the vector of independent current sources. This system is solved iteratively using the Newton-Raphson method, which linearizes the nonlinear functions around the current estimate and updates the solution via ΔV=−J−1F\Delta \mathbf{V} = -\mathbf{J}^{-1} \mathbf{F}, where J\mathbf{J} is the matrix of partial and F\mathbf{F} is the residual vector. The process continues until the residuals fall below specified tolerances, such as RELTOL for relative error. Transient analysis simulates the time-domain evolution of circuit variables by integrating the differential equations arising from capacitive and inductive elements in the device models. SPICE discretizes time into steps and approximates derivatives using implicit integration methods, transforming the problem into a sequence of nonlinear algebraic equations solved at each step via Newton-Raphson iteration. The default trapezoidal method models the of a variable x(t)x(t) as ∫tn−htnx(t) dt≈h2(x(tn)+x(tn−1))\int_{t_n - h}^{t_n} x(t) \, dt \approx \frac{h}{2} (x(t_n) + x(t_{n-1})), where hh is the time step, providing A-stability for stiff systems but potentially introducing numerical ringing in high-Q circuits. An alternative Gear method, introduced in SPICE3, uses backward difference formulas of second or higher order for improved accuracy in oscillatory responses, with the order adaptively selected up to six based on local estimates controlled by parameters like TRTOL. Time steps are fixed or controlled automatically to balance accuracy and efficiency. AC analysis evaluates the small-signal by linearizing the circuit around the DC operating point obtained from prior analysis. Nonlinear devices are replaced by their linearized equivalents, such as transconductances and s, yielding a solved in the using complex phasors. For each frequency point, SPICE computes node voltages as V(ω)=(G+jωC)−1I(ω)\mathbf{V}(\omega) = (\mathbf{G} + j\omega \mathbf{C})^{-1} \mathbf{I}(\omega), where C\mathbf{C} is the matrix and ω\omega is the , allowing extraction of magnitudes, phases, and transfer functions like gain and impedance. This enables efficient characterization of bandwidth, , and stability without simulating full transients. Beyond core analyses, SPICE supports specialized evaluations including noise analysis, which computes equivalent input noise spectral densities by summing contributions from devices (e.g., thermal noise 4kTγgmΔf4kT \gamma g_m \Delta f and KfIα/fβΔfK_f I^\alpha / f^\beta \Delta f) propagated through the ; , which calculates partial derivatives of outputs with respect to parameters using methods for ; and distortion analysis, assessing and products via small-signal nonlinear coefficients or, in extensions, techniques that solve multi-tone steady-state equations in the for large-signal RF circuits. Numerical instability in nonlinear iterations is mitigated by convergence enhancement techniques, such as source stepping, which gradually ramps independent sources from zero to their final values over multiple DC solutions to provide better initial guesses, and pseudo-transient methods, which introduce artificial time constants to damp oscillations and guide the solver toward the . These are invoked automatically or via options when iterations exceed limits, preventing failures in circuits with floating nodes or sharp nonlinearities.

Device Models and Parameters

SPICE employs a of mathematical models to represent the behavior of electronic components, ranging from simple linear elements to complex nonlinear devices. These models are defined through parameters that capture physical properties such as , characteristics, and operating conditions, enabling accurate of circuit performance across DC, transient, and AC analyses. The models are specified using dedicated syntax in the input , allowing users to select levels of based on the required and computational . Passive components in SPICE are modeled with straightforward equations that account for basic electrical properties and dependencies. Resistors are represented as linear elements with resistance value R, but can include voltage-dependent behavior via a expression or table lookup for nonlinear cases; dependence is incorporated through coefficients TC1 and TC2 in the equation R(T) = R(T0)[1 + TC1(T - T0) + TC2(T - T0)^2], where T0 is the nominal . Capacitors are defined by C, with support for initial conditions (IC) to set voltage at start, and junction capacitance modeled as CAP = CJ(L - NARROW)(W - NARROW) + 2 CJSW(L + W - 2 NARROW) for area and sidewall effects in integrated structures. Inductors use L, also with initial current conditions (IC), and can model for transformers via mutual inductance M. Diodes are simulated using the Shockley diode equation, which describes the current-voltage relationship as I=IS(eVD/(nVT)−1)I = I_S \left( e^{V_D / (n V_T)} - 1 \right), where ISI_S is the saturation current, nn is the emission coefficient, VDV_D is the diode voltage, and VT=kT/qV_T = kT/q is the thermal voltage with Boltzmann constant kk, temperature TT, and electron charge qq. This model includes series resistance RS, junction capacitance with parameters CJO (zero-bias capacitance), VJ (junction potential), and grading coefficient M, as well as temperature dependence through parameters like EG (bandgap energy) and XTI (temperature exponent for saturation current). Breakdown effects are captured by BV (reverse breakdown voltage) and IBV (current at breakdown). Bipolar junction transistors (BJTs) in SPICE utilize the Gummel-Poon model, an integral charge control formulation that extends the Ebers-Moll model to include high-current effects, base-width modulation (), and charge storage. The model operates at levels 1 through 3, with level 1 providing basic forward and reverse current gains; key parameters include BF (ideal maximum forward current gain β_F, default 100) for low-current beta and IS (transport saturation current, default 1.0 × 10^{-16} A) that scales the exponential collector current. Additional parameters such as VAF (forward Early voltage) account for the Early effect, where output conductance increases with collector-emitter voltage, while TF and TR model forward and reverse transit times for dynamic behavior. The model supports both NPN and PNP types with quasi-saturation effects at high bias levels. MOSFET models in SPICE progress from basic to advanced formulations to handle short-channel effects in modern technologies. The level 1 model, based on the Shichman-Hodges equations, assumes long-channel behavior and computes drain current in saturation as ID=12μCoxWL(VGS−VTH)2(1+λVDS)I_D = \frac{1}{2} \mu C_{ox} \frac{W}{L} (V_{GS} - V_{TH})^2 (1 + \lambda V_{DS}), where μ is carrier mobility, C_ox is capacitance per unit area, W/L is the channel , V_GS is gate-source voltage, V_TH is , and λ is the channel-length modulation parameter. Higher levels (2 and 3) add semi-empirical corrections for mobility degradation and . For contemporary nanoscale devices, BSIM models (levels 4 and beyond, up to BSIM4 and BSIM6) provide industry-standard accuracy, incorporating short-channel effects like velocity saturation, DIBL (drain-induced barrier lowering), and pocket implants through parameters such as VTH0 (zero-bias threshold), U0 (low-field mobility), and TOX ( thickness); BSIM4, for instance, uses a surface-potential-based core for robust scalability across process variations. SPICE supports through arbitrary dependent sources that use mathematical expressions for voltage or current, such as B sources defined as BXXX N+ N- I=expression (e.g., I = V(1)*V(2)) or V=expression, enabling compact representation of nonlinear or table-based behaviors without detailed internal circuitry. Subcircuits extend this by defining hierarchical macros with .SUBCKT and .ENDS statements, encapsulating complex elements like amplifiers as reusable blocks with instance parameters for customization. These feed into analyses like transient simulations to predict time-domain responses. Device parameters are specified via .MODEL statements, a SPICE-unique syntax that declares a model name, type (e.g., D for , NPN for BJT, NMOS for ), and parameter values, such as .MODEL MOD1 NMOS LEVEL=1 KP=100u VTO=0.7, where LEVEL selects the model complexity, KP is (μ C_ox), and VTO is zero-bias . This format allows sharing models across multiple instances while supporting temperature scaling and geometric scaling factors like SCALE for area adjustments.

Input Formats and Output Visualization

SPICE simulations are primarily defined through text-based files, which describe the circuit , components, and directives in a structured, human-readable format. Each line in the netlist typically specifies a component, such as a named R1 connected between nodes 1 and 2 with a value of 1 kΩ, written as R1 1 2 1k. Nodes represent electrical connections, with node 0 conventionally serving as the global ground. The netlist also includes .CONTROL statements to orchestrate runs, such as specifying input files or setting global parameters. Many modern SPICE-compatible tools integrate interfaces to simplify circuit definition, automatically generating the underlying from graphical elements. For instance, provides a built-in schematic editor where users draw components and wires, which the software converts to a SPICE for . Similarly, Qucs offers a for schematic entry, supporting SPICE through its integration with simulators like , allowing users to visualize and edit circuits before generating the text-based description. Control statements direct the types of analyses performed, with common examples including .OP for DC operating point analysis, which computes steady-state node voltages and currents, and .TRAN for transient analysis, such as .TRAN 1n 1u to simulate over a time span from 0 to 1 µs with a 1 ns print interval. Output selection is managed via statements like .PROBE in variants such as , which specifies vectors (e.g., node voltages) to save from the simulation. These directives ensure focused computation and data capture without unnecessary overhead. Simulation results are stored in raw data files, typically with a .raw extension, available in binary or ASCII formats containing time-domain or frequency-domain vectors. Visualization occurs through post-processing tools like , the original interactive plotter bundled with Berkeley SPICE3, which generates waveforms, XY plots, and Bode diagrams from the .raw data. For example, Nutmeg can display voltage versus time traces from a .TRAN run or magnitude-phase plots from .AC analysis. Post-processing extends analysis capabilities, such as applying Fourier transforms to transient outputs via the .FOUR statement to extract content at a specified , or generating statistical plots for simulations by varying parameters like tolerances and plotting distributions of key metrics. In AC analysis, the .raw file directly provides data for magnitude and phase visualization. Evolutions in open-source variants like and Xyce include enhanced output options for scripting and integration, such as exporting simulation data in structured formats like CSV or TECPLOT for further processing, though direct or XML exports are facilitated through wrapper tools like PySpice, which convert .raw contents to for Python-based automation. These features support advanced workflows in large-scale simulations.

Applications and Extensions

Core Uses in Circuit Design

SPICE serves as a foundational tool in design for verifying functionality, optimizing performance, and predicting behavior prior to physical prototyping. In analog (IC) design, it enables precise analysis of operating conditions and dynamic responses, allowing engineers to refine topologies iteratively. At the board level, SPICE supports evaluations of environmental effects and signal quality, integrating seamlessly into broader (EDA) workflows. This versatility stems from its ability to model complex interactions using differential equations, ensuring reliable designs across scales from ICs to printed circuit boards (PCBs). In analog IC design, SPICE is essential for point verification and analysis of . The DC operating point analysis (.OP directive) computes steady-state voltages and currents at nodes, confirming transistors operate in intended regions like saturation for MOSFETs in a common-source (CS) amplifier, where simulations adjust parameters such as gate width (W) to achieve target drain current (I_D ≈ 0.45 mA) and output voltage (V_O ≈ 1.39 V). For (BJT) common-emitter (CE) amplifiers, it verifies collector current (I_C ≈ 0.5 mA) and assesses stability against variations in current gain (BF). is evaluated via AC analysis (.AC directive), which linearizes the circuit around the bias point to plot gain versus frequency; for instance, a CMOS CS amplifier yields a midband gain (A_M) of 9.55 V/V and 3-dB bandwidth (BW) of 122.1 MHz, highlighting effects like the capacitance on high-frequency roll-off. These simulations, as demonstrated in educational and design examples, prevent issues like or insufficient bandwidth in . For mixed-signal circuits, SPICE incorporates digital elements through extensions like XSPICE, enabling hybrid analog-digital simulations without separate tools. XSPICE adds event-driven digital models that interface with SPICE's analog solver, using code-level modeling for behavioral accuracy and speed; digital gates, for example, trigger only on state changes, reducing computation for large systems. In implementations, this supports mixed-mode analysis of interfaces like analog-to-digital converters (ADCs), where analog SPICE models handle continuous signals and XSPICE primitives simulate digital logic with predefined truth tables. This integration is critical for verifying timing and noise coupling in systems-on-chip (SoCs), as seen in open-source flows combining SPICE with simulations. At the PCB and board level, SPICE facilitates , noise, and analyses to ensure robust system performance. modeling uses equivalent RC networks to represent heat flow, simulating junction temperatures in power devices like eXtreme Switches on JEDEC-standard PCBs; for a multi-channel switch, it predicts steady-state thermal impedance with <7% error compared to measurements, accounting for cross-coupling between channels. Noise analysis (.NOISE directive) quantifies contributions from resistors and active devices, generating spectral density plots to identify dominant sources in amplifiers or filters, applicable to PCB layouts where parasitic effects amplify interference. checks employ transient simulations with transmission line models to detect reflections and crosstalk; SPICE models predict eye diagrams and jitter in high-speed buses, outperforming simpler IBIS models for detailed analog effects in PCB traces. These capabilities help mitigate failures in dense boards, such as overheating or signal degradation. SPICE integrates deeply into EDA design flows, particularly with tools like Cadence Virtuoso, for iterative analog IC simulation. Virtuoso's Analog Design Environment (ADE) suite embeds SPICE-compatible simulators (e.g., Spectre or HSPICE) to run thousands of analyses, from schematic capture to layout extraction, using unified parsers for netlists and Verilog-A models. This allows automated sweeps of parameters like transistor sizing during optimization, accelerating verification in custom IC workflows by linking simulation results to layout parasitics. Such integration reduces design cycles, as engineers iterate bias and response analyses within a single environment. Case studies illustrate SPICE's practical impact, such as op-amp stability analysis and power supply ripple prediction. For op-amp stability, two SPICE methods break the feedback loop: one at the output to measure via Bode plots (e.g., >45° for a voltage follower with capacitive load), and another injecting a test signal to compute loop gain directly, revealing from load in a non-inverting . In power supplies, average and switching models predict ripple in buck converters; a voltage-mode shows output ripple <100 mV at 50 kHz switching with proper compensation, while current-mode flyback examples stabilize at 60° to avoid subharmonic oscillations. These analyses, validated against prototypes, guide component selection and feedback . In , SPICE fosters virtual prototyping to teach circuit at universities. Tools like enable students to simulate and tweak designs, such as ADCs, observing trade-offs in gain, noise, and bandwidth through iterative reflections; in a project-based course, 40% of student analyses linked simulations to theoretical concepts, enhancing problem-solving and . This approach replaces costly labs with accessible prototyping, building intuition for real-world behaviors like frequency responses in amplifiers.

Applications Outside Electronics

SPICE's equation-solving framework, originally developed for electrical circuit analysis, has been adapted for simulations in diverse fields by leveraging electrical analogies to model physical phenomena. These adaptations map non-electrical variables to circuit elements—such as voltage to potential difference, current to flow rate, resistance to frictional losses, to compliance, and to —enabling the use of SPICE's numerical solvers for transient, DC, and AC analyses in analogous systems. In thermal and mechanical modeling, SPICE employs lumped-parameter analogies to simulate and dynamic systems. For thermal applications, thermal resistance is equated to electrical resistance, while corresponds to electrical capacitance, allowing simulations of heat dissipation in materials or devices using standard resistor-capacitor networks. For instance, thermoelectric elements like Peltier cells are modeled by coupling electrical and thermal domains, where temperature gradients drive currents analogous to voltage sources. In mechanical contexts, mass-spring-damper systems are represented as inductor-resistor-capacitor circuits, with inductance modeling inertial effects (e.g., ) and resistance capturing . Fluid dynamics simulations draw similar analogies, treating fluid as inductance, pressure drops as voltage, and flow resistance as electrical resistance, though these are less common due to the need for distributed models in complex flows. Biological modeling benefits from SPICE's ability to handle nonlinear differential equations, particularly in . The Hodgkin-Huxley model of neuronal action potentials, which describes dynamics through voltage-gated conductances, is implemented as subcircuits in SPICE, with as voltage and ionic currents as branch currents. This approach simulates excitable membrane behavior in single neurons or small networks, capturing phenomena like spike generation and propagation. Adaptations include equivalent circuit diagrams for squid axon patches, where sodium and potassium conductances are modeled as variable resistors controlled by gating variables solved via SPICE's integrators. Modified SPICE versions optimize for detailed neuronal simulations, enabling analysis of synaptic interactions and network dynamics. In control systems, SPICE facilitates PID (proportional-integral-derivative) controller design and tuning through its s-domain (Laplace) analysis capabilities. AC simulations in the allow evaluation of stability margins, phase shifts, and gain responses for feedback loops, where the PID transfer function H(s)=Kp+Kis+KdsH(s) = K_p + \frac{K_i}{s} + K_d s is realized as an op-amp subcircuit. Tuning involves parametric sweeps to adjust gains for desired overshoot and settling times, often starting from Ziegler-Nichols rules adapted to simulated step responses. This method is particularly useful for analog control hardware verification, bridging to digital implementations. Post-2020 developments have extended SPICE to emerging areas like approximations and AI-accelerated modeling. For quantum simulations, classical SPICE emulates superconducting circuits such as transmons in the dispersive regime, approximating dynamics with nonlinear inductors and capacitors to analyze transmission signals without full quantum solvers. Frameworks also replicate universal gates (e.g., Hadamard, CNOT) using behavioral models for noise-inclusive emulation. In AI integration, neural networks assist fitting by on SPICE outputs to optimize device models, reducing simulation time for complex fits; dual neural architectures combine with SPICE for fast transistor-level predictions. These approaches leverage SPICE's compatibility with for hybrid classical-quantum and ML-enhanced workflows. Open-source variants like support custom models via XSPICE extensions, enabling behavioral code in C for non-electronic domains. In , integrates with tools like VPIphotonics Design Suite to simulate optoelectronic components, loading models for modulators and lasers at runtime. Acoustics applications use analogous models for wave propagation, though specific custom implementations remain niche. These extensions allow user-defined differential equations for phenomena like photonic waveguides or acoustic resonators. Despite these adaptations, SPICE faces limitations for large non-electronic systems. Its lumped-element assumption struggles with distributed effects in expansive domains like multiphysics thermal-fluid interactions, leading to convergence issues and high computational demands for thousands of nodes. Specialized solvers like outperform SPICE in such cases by employing finite element methods for coupled, spatially resolved simulations, though SPICE remains efficient for smaller, analogy-based prototypes.

References

  1. https://bwrcs.eecs.berkeley.edu/
  2. https://ethw.org/Milestones:SPICE_%28Simulation_Program_with_Integrated_Circuit_Emphasis%29%2C_1969-1970
  3. https://www.allaboutcircuits.com/textbook/reference/chpt-7/history-of-spice/
  4. https://www.analog.com/en/resources/design-tools-and-calculators/ltspice-simulator.html
  5. https://ngspice.sourceforge.io/
  6. https://www.ni.com/en/shop/electronic-test-instrumentation/application-software-for-electronic-test-and-instrumentation-category/what-is-multisim/spice-simulation-fundamentals/spice-simulation-overview.html
  7. https://www.nsf.gov/impacts/semiconductors
  8. https://www.eng.auburn.edu/~wilambm/pap/1997/SBook/1_INT
  9. https://www2.eecs.berkeley.edu/Pubs/TechRpts/1973/22871.html
  10. https://www.omega-enterprises.net/The%20Origins%20of%20SPICE.html
  11. https://ethw.org/w/images/2/2e/The-Origins-of-SPICE.pdf
  12. https://www2.eecs.berkeley.edu/Pubs/TechRpts/1973/ERL-382.pdf
  13. https://semiwiki.com/eda/1568-a-brief-history-of-spice/
  14. http://www.ece.umn.edu/~harjani/courses/common/spice2G6.pdf
  15. https://www2.eecs.berkeley.edu/Pubs/TechRpts/1981/ERL-m-81-31.pdf
  16. https://ieee-cas.org/files/ieeecass/2022-01/a_short_history_of_circuits_and_systems-_ebook-_web.pdf
  17. https://ethw.org/w/images/d/db/CNSV-0906-Nagel.pdf
  18. https://github.com/ngspice/ngspice
  19. https://ngspice.sourceforge.io/news.html
  20. https://ngspice.sourceforge.io/shared.html
  21. https://pyspice.fabrice-salvaire.fr/releases/v1.4/
  22. https://xyce.sandia.gov/about-xyce/
  23. https://www.osti.gov/servlets/purl/1592255
  24. https://xyce.sandia.gov/
  25. https://semiwiki.com/forum/threads/announcing-the-open-source-release-of-the-xyce-circuit-simulator.3416/
  26. https://ra3xdh.github.io/
  27. https://github.com/ra3xdh/qucs_s
  28. https://ngspice.sourceforge.io/osdi.html
  29. https://arxiv.org/html/2404.02911v1
  30. https://ngspice.sourceforge.io/faq.html
  31. https://www.analog.com/en/resources/technical-articles/how-to-model-statistical-tolerance-analysis.html
  32. https://ez.analog.com/design-tools-and-calculators/ltspice/a/faqs-docs/FD559/what-s-new-in-ltspice-24
  33. https://www.cadence.com/en_US/home/tools/pcb-design-and-analysis/analog-mixed-signal-simulation/pspice.html
  34. https://www.cadence.com/content/dam/cadence-www/global/en_US/documents/tools/pcb-design-analysis/allegro-pspice-simulator-ds.pdf
  35. https://www.cadence.com/en_US/home/tools/custom-ic-analog-rf-design/circuit-simulation/spectre-ams-designer.html
  36. https://www.cadence.com/en_US/home/resources/datasheets/spectre-simulation-platform-ds.html
  37. https://www.synopsys.com/content/dam/synopsys/verification/datasheets/hspice-ds.pdf
  38. https://news.synopsys.com/home?item=122858
  39. https://www.synopsys.com/content/dam/synopsys/implementation&signoff/white-papers/PrimeTime_AdvancedOCV_WP.pdf
  40. https://www.mordorintelligence.com/industry-reports/electronic-design-automation-eda-tools-market
  41. https://www2.eecs.berkeley.edu/Pubs/TechRpts/1973/ERL-m-382.pdf
  42. https://www.researchgate.net/publication/3348837_Overview_of_SPICE-like_circuit_simulation_algorithms
  43. http://www.spiceopus.si/download/spice3_manual.pdf
  44. http://ieeexplore.ieee.org/document/1329083/
  45. https://nanohub.org/app/site/archive/Spice3F4_Manual.pdf
  46. https://www.kevinaylward.co.uk/ee/voltagecontrolledbipolar/gummel-poon.pdf
  47. https://bsim.berkeley.edu/models/bsim4/
  48. https://web.stanford.edu/class/ee133/handouts/general/spice_ref.pdf
  49. https://www.ni.com/en/shop/electronic-test-instrumentation/application-software-for-electronic-test-and-instrumentation-category/what-is-multisim/spice-simulation-fundamentals/spice-simulation-and-control-statements.html
  50. https://bwrcs.eecs.berkeley.edu/Classes/IcBook/SPICE/MANUALS/nutmeg.html
  51. https://ngspice.sourceforge.io/ngspice-control-language-tutorial.html
  52. https://xyce.sandia.gov/files/xyce/Xyce_Users_Guide_7.8.pdf
  53. https://learninglink.oup.com/protected/files/content/file/1579782004774-Sedra8e_AppB.pdf
  54. https://www.powerelectronicsnews.com/guide-to-spice-simulation-for-circuit-analysis-and-design-part-7-the-ac-analysis/
  55. https://ngspice.sourceforge.io/xspiceusage.html
  56. https://nmg.gitlab.io/ngspice-manual/mixed-modeandbehavioralmodelingwithxspice.html
  57. https://www.nxp.com/docs/en/application-note/AN4146.pdf
  58. https://www.embedded.com/guide-to-spice-simulation-for-circuit-analysis-and-design-part-20-noise-analysis/
  59. https://www.analog.com/en/resources/analog-dialogue/articles/spice-vs-ibis-choosing-the-more-appropriate-model-for-your-circuit.html
  60. https://www.cadence.com/en_US/home/explore/spice-simulation.html
  61. https://www.edn.com/two-methods-for-spice-based-amplifier-stability-analysis/
  62. https://www.onsemi.com/pub/collateral/tnd349-d.pdf
  63. https://www.mdpi.com/2227-7102/15/8/1045
  64. https://iaeme.com/MasterAdmin/Journal_uploads/IJMET/VOLUME_9_ISSUE_2/IJMET_09_02_047.pdf
  65. https://www.researchgate.net/publication/3849593_SPICE_model_of_thermoelectric_elements_including_thermal_effects
  66. https://techweb.rohm.com/product/circuit-design/simulation/8390/
  67. https://ieeexplore.ieee.org/document/632873/
  68. https://www.youtube.com/watch?v=LJ_8upMjNbk
  69. https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13303/1330304/Constructing-equivalent-Hodgkin-Huxley-neuron-spice-model-of-the-subthalamic/10.1117/12.3042533.full
  70. https://digitalcommons.latech.edu/cgi/viewcontent.cgi?article=1535&context=dissertations
  71. https://pubmed.ncbi.nlm.nih.gov/3841014/
  72. https://link.springer.com/article/10.1007/BF00197316
  73. https://www.ecircuitcenter.com/Circuits/pid1/pid1.htm
  74. https://iopscience.iop.org/article/10.35848/1882-0786/acc3d8
  75. https://www.researchgate.net/publication/369206860_Classical_SPICE_simulation_of_superconducting_quantum_circuits
  76. https://d-nb.info/1363740784/34
  77. https://www.researchgate.net/publication/394263548_ANN-Assisted_SPICE_Model_Solutions
  78. https://www.vpiphotonics.com/News/2025/DesignSuite_116_News.php
  79. https://forum.kicad.info/t/exploring-the-underused-potential-of-ngspice-xspice-code-models-an-alternative-to-qspice/49300
  80. https://www.ecircuitcenter.com/SpiceTopics/Limitations.htm
  81. https://www.ariat-tech.com/blog/spice-primary-dynamics%2Capplications%2Cand-advantages.html
  82. https://www.mdpi.com/2674-0729/1/1/6
  83. https://www.sciencedirect.com/science/article/pii/S2665917424003921
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