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Integer factorization records

Integer factorization records is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Integer factorization records rather than just read about it. In short: Integer factorization is the process of determining which prime numbers divide a given positive integer. Doing this quickly has applications in cryptography.

Key takeaways

  • Integer factorization records belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Integer factorization records to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Integer factorization records from memory before moving on to harder problems.

Reference excerpt

Integer factorization is the process of determining which prime numbers divide a given positive integer. Doing this quickly has applications in cryptography. The difficulty depends on both the size and form of the number and its prime factors; it is currently very difficult to factorize large semiprimes (and, indeed, most numbers that have no small factors).

Numbers of a general form The first enormous distributed factorisation was RSA-129, a 129-digit challenge number described in the Scientific American article of 1977 which first popularised the RSA cryptosystem. It was factorised between September 1993 and April 1994, using MPQS, with relations contributed by about 600 people through the internet, and the final stages of the calculation performed on a MasPar supercomputer at Bell Labs. Between January and August 1999, RSA-155, a 155-digit challenge number prepared by the RSA company, was factorised using GNFS with relations again contributed by a large group, and the final stages of the calculation performed in just over nine days on the Cray C916 supercomputer at the SARA Amsterdam Academic Computer Center. In January 2002, it was announced the factorisation of a 158-digit cofactor of 2953 + 1, using a couple of months on about 25 PCs at the University of Bonn, with the final stages done using a cluster of six Pentium-III PCs. In April 2003, the same team factored the 160-digit RSA-160 using about a hundred CPUs at BSI, with the final stages of the calculation done using 25 processors of an SGI Origin supercomputer. The 576-bit (174-digit) RSA-576 was factored by members of the NFSNET collaboration in December 2003, using resources at BSI and the University of Bonn; soon afterwards it was announced a group factored a 164-digit cofactor of 21826 + 1. A 176-digit cofactor of 11281 + 1 was factored between February and May 2005 using machines at NTT and Rikkyo University in Japan. The 663-bit (200-digit) RSA-200 challenge number was factored between December 2003 and May 2005, using a cluster of 80 Opteron processors at BSI in Germany; the announcement was made on 9 May 2005. They later factored the slightly smaller RSA-640 challenge number in November 2005. On December 12, 2009, a team including researchers from the CWI, the EPFL, INRIA and NTT in addition to the authors of the previous record factored RSA-768, a 232-digit semiprime. They used the equivalent of almost 2000 years of computing on a single core 2.2 GHz AMD Opteron. In November 2019, the 795-bit (240-digit) RSA-240 was factored. In February 2020, the factorization of the 829-bit (250-digit) RSA-250 was completed.

Numbers of a special form 12151 − 1, of 542 bits (163 digits), was factored between April and July 1993 by a team at CWI and Oregon State University. 2773 + 1, of 774 bits (233 digits), was factored between April and November 2000 by 'The Cabal', with the matrix step done over 250 hours on the Cray also used for RSA-155. 2809 − 1, of 809 bits (244 digits), had its factorisation announced at the start of January 2003. Sieving was done at the CWI, at the Scientific Computing Institute and the Pure Mathematics Department at Bonn University, and using private resources. The linear algebra step was done at SARA in Amsterdam. 6353 − 1, of 911 bits (275 digits), was factored between September 2005 and January 2006 using SNFS. 21039 − 1, of 1039 bits (313 digits) (though a factor of 23 bits was already known) was factored between September 2006 and May 2007 by a group at NTT, EPFL and the University of Bonn. 21061 − 1, of 1061 bits (320 digits) was factored between early 2011 and 4 August 2012 by a group at CSU Fullerton, using the nfs@home BOINC project for about 300 CPU-years of sieving; the linear algebra was run at the Trestles cluster at SDSC and the Lonestar cluster at TACC and needed an additional 35 CPU-years. All unfactored parts of the numbers 2n − 1 with n between 1000 and 1200 were factored by a multiple-number-sieve approach in which much of the sieving step could be done simultaneously for multiple numbers, starting in 2010. To be precise, n = 1081 (326 digits) was completed on 11 March 2013; n = 1111 (335 digits) on 13 June 2013; n = 1129 (340 digits) on 20 September 2013; n = 1153 (348 digits) on 28 October 2013; n=1159 (349 digits) on 9 February 2014; n = 1177 (355 digits) on 29 May 2014, n = 1193 (360 digits) on 22 August 2014, and n = 1199 (361 digits) on 11 December 2014; the first detailed announcement was made in late August 2014. The total effort for the project is of the order of 7500 CPU-years on 2.2 GHz Opterons, with roughly 5700 years spent sieving and 1800 years on linear algebra.

Largest penultimate prime factor The record of the prime factor other than the ultimate prime factor has 155 decimal digits; it is a prime factor of 12311−1.

Comparison to efforts by individuals As of the end of 2007, thanks to the constant decline in memory prices, the ready availability of multi-core 64-bit computers, and the availability of the efficient sieving code via ggnfs and of robust open-source software such as msieve for the finishing stages, special-form numbers of up to 750 bits (226 digits) and general-form numbers of up to about 520 bits (157 digits) can be factored in a few months on a few PCs by a single person without any special mathematical experience. These bounds increase to about 950 bits (286 digits) and 600 bits (181 digits) if it were possible to secure the collaboration of a few dozen PCs for sieving; currently the amount of memory and the CPU power of a single machine for the finishing stage are equal barriers to progress. In 2009, a 512-bit (155-digit) RSA key was factored. This key had been used to sign the TI-83 graphing calculator using software found on the internet; this eventually led to the Texas Instruments signing key controversy. In September 2013, the 696-bit (210-digit) RSA-210 was factored using institutional resources; between March 2013 and October 2014, another 210-digit number (the 117th term in the home prime sequence starting with 49), using $7600 worth of processing time on Amazon EC2 machines for the sieving, and four months on a dual Xeon E5-2687W v1 for the linear algebra.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Integer factorization records

Start with the simplest possible case. Write down what Integer factorization records claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Integer factorization records before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Integer factorization records ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Integer factorization records

In research
Integer factorization records appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Integer factorization records in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Integer factorization records is common in secondary-school and first-year university syllabi. It links to neighbouring topics Integer factorization algorithms, World records, so understanding it makes those chapters shorter.
In everyday life
Look for Integer factorization records outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Integer factorization records in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Integer factorization records means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Integer factorization records out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Integer factorization records in simple terms?

Integer factorization is the process of determining which prime numbers divide a given positive integer. Doing this quickly has applications in cryptography.

Why does Integer factorization records matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Integer factorization records?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Integer factorization records.

Tags

  • Integer factorization algorithms
  • World records

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