WHAT IS the BEST APPROACH to COUNTING PRIMES? Andrew Granville 1. How Many Primes Are There? Predictions You Have Probably Seen
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An Amazing Prime Heuristic.Pdf
This document has been moved to https://arxiv.org/abs/2103.04483 Please use that version instead. AN AMAZING PRIME HEURISTIC CHRIS K. CALDWELL 1. Introduction The record for the largest known twin prime is constantly changing. For example, in October of 2000, David Underbakke found the record primes: 83475759 264955 1: · The very next day Giovanni La Barbera found the new record primes: 1693965 266443 1: · The fact that the size of these records are close is no coincidence! Before we seek a record like this, we usually try to estimate how long the search might take, and use this information to determine our search parameters. To do this we need to know how common twin primes are. It has been conjectured that the number of twin primes less than or equal to N is asymptotic to N dx 2C2N 2C2 2 2 Z2 (log x) ∼ (log N) where C2, called the twin prime constant, is approximately 0:6601618. Using this we can estimate how many numbers we will need to try before we find a prime. In the case of Underbakke and La Barbera, they were both using the same sieving software (NewPGen1 by Paul Jobling) and the same primality proving software (Proth.exe2 by Yves Gallot) on similar hardware{so of course they choose similar ranges to search. But where does this conjecture come from? In this chapter we will discuss a general method to form conjectures similar to the twin prime conjecture above. We will then apply it to a number of different forms of primes such as Sophie Germain primes, primes in arithmetic progressions, primorial primes and even the Goldbach conjecture. -
Abstract in This Paper, D-Strong and Almost D-Strong Near-Rings Ha
Periodica Mathematica Hungarlca Vol. 17 (1), (1986), pp. 13--20 D-STRONG AND ALMOST D-STRONG NEAR-RINGS A. K. GOYAL (Udaipur) Abstract In this paper, D-strong and almost D-strong near-rings have been defined. It has been proved that if R is a D-strong S-near ring, then prime ideals, strictly prime ideals and completely prime ideals coincide. Also if R is a D-strong near-ring with iden- tity, then every maximal right ideal becomes a maximal ideal and moreover every 2- primitive near-ring becomes a near-field. Several properties, chain conditions and structure theorems have also been discussed. Introduction In this paper, we have generalized some of the results obtained for rings by Wong [12]. Corresponding to the prime and strictly prime ideals in near-rings, we have defined D-strong and almost D-strong near-rings. It has been shown that a regular near-ring having all idempotents central in R is a D-strong and hence almost D-strong near-ring. If R is a D-strong S-near ring, then it has been shown that prime ideals, strictly prime ideals and com- pletely prime ideals coincide and g(R) = H(R) ~ ~(R), where H(R) is the intersection of all strictly prime ideals of R. Also if R is a D-strong near-ring with identity, then every maximal right ideal becomes a maximal ideal and moreover every 2-primitive near-ring becomes a near-field. Some structure theorems have also been discussed. Preliminaries Throughout R will denote a zero-symmetric left near-ring, i.e., R -- Ro in the sense of Pilz [10]. -
A Short and Simple Proof of the Riemann's Hypothesis
A Short and Simple Proof of the Riemann’s Hypothesis Charaf Ech-Chatbi To cite this version: Charaf Ech-Chatbi. A Short and Simple Proof of the Riemann’s Hypothesis. 2021. hal-03091429v10 HAL Id: hal-03091429 https://hal.archives-ouvertes.fr/hal-03091429v10 Preprint submitted on 5 Mar 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A Short and Simple Proof of the Riemann’s Hypothesis Charaf ECH-CHATBI ∗ Sunday 21 February 2021 Abstract We present a short and simple proof of the Riemann’s Hypothesis (RH) where only undergraduate mathematics is needed. Keywords: Riemann Hypothesis; Zeta function; Prime Numbers; Millennium Problems. MSC2020 Classification: 11Mxx, 11-XX, 26-XX, 30-xx. 1 The Riemann Hypothesis 1.1 The importance of the Riemann Hypothesis The prime number theorem gives us the average distribution of the primes. The Riemann hypothesis tells us about the deviation from the average. Formulated in Riemann’s 1859 paper[1], it asserts that all the ’non-trivial’ zeros of the zeta function are complex numbers with real part 1/2. 1.2 Riemann Zeta Function For a complex number s where ℜ(s) > 1, the Zeta function is defined as the sum of the following series: +∞ 1 ζ(s)= (1) ns n=1 X In his 1859 paper[1], Riemann went further and extended the zeta function ζ(s), by analytical continuation, to an absolutely convergent function in the half plane ℜ(s) > 0, minus a simple pole at s = 1: s +∞ {x} ζ(s)= − s dx (2) s − 1 xs+1 Z1 ∗One Raffles Quay, North Tower Level 35. -
Neural Networks and the Search for a Quadratic Residue Detector
Neural Networks and the Search for a Quadratic Residue Detector Michael Potter∗ Leon Reznik∗ Stanisław Radziszowski∗ [email protected] [email protected] [email protected] ∗ Department of Computer Science Rochester Institute of Technology Rochester, NY 14623 Abstract—This paper investigates the feasibility of employing This paper investigates the possibility of employing ANNs artificial neural network techniques for solving fundamental in the search for a solution to the quadratic residues (QR) cryptography problems, taking quadratic residue detection problem, which is defined as follows: as an example. The problem of quadratic residue detection Suppose that you have two integers a and b. Then a is is one which is well known in both number theory and a quadratic residue of b if and only if the following two cryptography. While it garners less attention than problems conditions hold: [1] such as factoring or discrete logarithms, it is similar in both 1) The greatest common divisor of a and b is 1, and difficulty and importance. No polynomial–time algorithm is 2) There exists an integer c such that c2 ≡ a (mod b). currently known to the public by which the quadratic residue status of one number modulo another may be determined. This The first condition is satisfied automatically so long as ∗ work leverages machine learning algorithms in an attempt to a 2 Zb . There is, however, no known polynomial–time (in create a detector capable of solving instances of the problem the number of bits of a and b) algorithm for determining more efficiently. A variety of neural networks, currently at the whether the second condition is satisfied. -
A Scalable System-On-A-Chip Architecture for Prime Number Validation
A SCALABLE SYSTEM-ON-A-CHIP ARCHITECTURE FOR PRIME NUMBER VALIDATION Ray C.C. Cheung and Ashley Brown Department of Computing, Imperial College London, United Kingdom Abstract This paper presents a scalable SoC architecture for prime number validation which targets reconfigurable hardware This paper presents a scalable SoC architecture for prime such as FPGAs. In particular, users are allowed to se- number validation which targets reconfigurable hardware. lect predefined scalable or non-scalable modular opera- The primality test is crucial for security systems, especially tors for their designs [4]. Our main contributions in- for most public-key schemes. The Rabin-Miller Strong clude: (1) Parallel designs for Montgomery modular arith- Pseudoprime Test has been mapped into hardware, which metic operations (Section 3). (2) A scalable design method makes use of a circuit for computing Montgomery modu- for mapping the Rabin-Miller Strong Pseudoprime Test lar exponentiation to further speed up the validation and to into hardware (Section 4). (3) An architecture of RAM- reduce the hardware cost. A design generator has been de- based Radix-2 Scalable Montgomery multiplier (Section veloped to generate a variety of scalable and non-scalable 4). (4) A design generator for producing hardware prime Montgomery multipliers based on user-defined parameters. number validators based on user-specified parameters (Sec- The performance and resource usage of our designs, im- tion 5). (5) Implementation of the proposed hardware ar- plemented in Xilinx reconfigurable devices, have been ex- chitectures in FPGAs, with an evaluation of its effective- plored using the embedded PowerPC processor and the soft ness compared with different size and speed tradeoffs (Sec- MicroBlaze processor. -
Bayesian Perspectives on Mathematical Practice
Bayesian perspectives on mathematical practice James Franklin University of New South Wales, Sydney, Australia In: B. Sriraman, ed, Handbook of the History and Philosophy of Mathematical Practice, Springer, 2020. Contents 1. Introduction 2. The relation of conjectures to proof 3. Applied mathematics and statistics: understanding the behavior of complex models 4. The objective Bayesian perspective on evidence 5. Evidence for and against the Riemann Hypothesis 6. Probabilistic relations between necessary truths? 7. The problem of induction in mathematics 8. Conclusion References Abstract Mathematicians often speak of conjectures as being confirmed by evi- dence that falls short of proof. For their own conjectures, evidence justifies further work in looking for a proof. Those conjectures of mathematics that have long re- sisted proof, such as the Riemann Hypothesis, have had to be considered in terms of the evidence for and against them. In recent decades, massive increases in com- puter power have permitted the gathering of huge amounts of numerical evidence, both for conjectures in pure mathematics and for the behavior of complex applied mathematical models and statistical algorithms. Mathematics has therefore be- come (among other things) an experimental science (though that has not dimin- ished the importance of proof in the traditional style). We examine how the evalu- ation of evidence for conjectures works in mathematical practice. We explain the (objective) Bayesian view of probability, which gives a theoretical framework for unifying evidence evaluation in science and law as well as in mathematics. Nu- merical evidence in mathematics is related to the problem of induction; the occur- rence of straightforward inductive reasoning in the purely logical material of pure mathematics casts light on the nature of induction as well as of mathematical rea- soning. -
Diffie-Hellman Key Exchange
Public Key Cryptosystems - Diffie Hellman Public Key Cryptosystems - Diffie Hellman Get two parties to share a secret number that no one else knows Public Key Cryptosystems - Diffie Hellman Get two parties to share a secret number that no one else knows Receiver Sender Public Key Cryptosystems - Diffie Hellman Get two parties to share a secret number that no one else knows Can only use an insecure communications channel for exchange Receiver Sender Attacker Public Key Cryptosystems - Diffie Hellman Get two parties to share a secret number that no one else knows Can only use an insecure communications channel for exchange p,g Receiver Sender p: prime & (p-1)/2 prime g: less than p n = gk mod p Attacker for all 0<n<p and some k (see http://gauss.ececs.uc.edu/Courses/c6053/lectures/Math/Group/group.html) Public Key Cryptosystems - Diffie Hellman A safe prime p: p = 2q + 1 where q is also prime Example: 479 = 2*239 + 1 If p is a safe prime, then p-1 has large prime factor, namely q. If all the factors of p-1 are less than logcp, then the problem of solving the discrete logarithm modulo p is in P (it©s easy). Therefore, for cryptosystems based on discrete logarithm (such as Diffie-Hellman) it is required that p-1 has at least one large prime factor. Public Key Cryptosystems - Diffie Hellman A strong prime p: p is large p-1 has large prime factors (p = aq+1 for integer a and prime q) q-1 has large prime factors (q = br+1 for integer b, prime r) p+1 has large prime factors. -
2 Primes Numbers
V55.0106 Quantitative Reasoning: Computers, Number Theory and Cryptography 2 Primes Numbers Definition 2.1 A number is prime is it is greater than 1, and its only divisors are itself and 1. A number is called composite if it is greater than 1 and is the product of two numbers greater than 1. Thus, the positive numbers are divided into three mutually exclusive classes. The prime numbers, the composite numbers, and the unit 1. We can show that a number is composite numbers by finding a non-trivial factorization.8 Thus, 21 is composite because 21 = 3 7. The letter p is usually used to denote a prime number. × The first fifteen prime numbers are 2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41 These are found by a process of elimination. Starting with 2, 3, 4, 5, 6, 7, etc., we eliminate the composite numbers 4, 6, 8, 9, and so on. There is a systematic way of finding a table of all primes up to a fixed number. The method is called a sieve method and is called the Sieve of Eratosthenes9. We first illustrate in a simple example by finding all primes from 2 through 25. We start by listing the candidates: 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25 The first number 2 is a prime, but all multiples of 2 after that are not. Underline these multiples. They are eliminated as composite numbers. The resulting list is as follows: 2, 3, 4,5,6,7,8,9,10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,25 The next number not eliminated is 3, the next prime. -
Prime Number Theorem
Prime Number Theorem Bent E. Petersen Contents 1 Introduction 1 2Asymptotics 6 3 The Logarithmic Integral 9 4TheCebyˇˇ sev Functions θ(x) and ψ(x) 11 5M¨obius Inversion 14 6 The Tail of the Zeta Series 16 7 The Logarithm log ζ(s) 17 < s 8 The Zeta Function on e =1 21 9 Mellin Transforms 26 10 Sketches of the Proof of the PNT 29 10.1 Cebyˇˇ sev function method .................. 30 10.2 Modified Cebyˇˇ sev function method .............. 30 10.3 Still another Cebyˇˇ sev function method ............ 30 10.4 Yet another Cebyˇˇ sev function method ............ 31 10.5 Riemann’s method ...................... 31 10.6 Modified Riemann method .................. 32 10.7 Littlewood’s Method ..................... 32 10.8 Ikehara Tauberian Theorem ................. 32 11ProofofthePrimeNumberTheorem 33 References 39 1 Introduction Let π(x) be the number of primes p ≤ x. It was discovered empirically by Gauss about 1793 (letter to Enke in 1849, see Gauss [9], volume 2, page 444 and Goldstein [10]) and by Legendre (in 1798 according to [14]) that x π(x) ∼ . log x This statement is the prime number theorem. Actually Gauss used the equiva- lent formulation (see page 10) Z x dt π(x) ∼ . 2 log t 1 B. E. Petersen Prime Number Theorem For some discussion of Gauss’ work see Goldstein [10] and Zagier [45]. In 1850 Cebyˇˇ sev [3] proved a result far weaker than the prime number theorem — that for certain constants 0 <A1 < 1 <A2 π(x) A < <A . 1 x/log x 2 An elementary proof of Cebyˇˇ sev’s theorem is given in Andrews [1]. -
Notes on the Prime Number Theorem
Notes on the prime number theorem Kenji Kozai May 2, 2014 1 Statement We begin with a definition. Definition 1.1. We say that f(x) and g(x) are asymptotic as x → ∞, f(x) written f ∼ g, if limx→∞ g(x) = 1. The prime number theorem tells us about the asymptotic behavior of the number of primes that are less than a given number. Let π(x) be the number of primes numbers p such that p ≤ x. For example, π(2) = 1, π(3) = 2, π(4) = 2, etc. The statement that we will try to prove is as follows. Theorem 1.2 (Prime Number Theorem, p. 382). The asymptotic behavior of π(x) as x → ∞ is given by x π(x) ∼ . log x This was originally observed as early as the 1700s by Gauss and others. The first proof was given in 1896 by Hadamard and de la Vall´ee Poussin. We will give an overview of simplified proof. Most of the material comes from various sections of Gamelin – mostly XIV.1, XIV.3 and XIV.5. 2 The Gamma Function The gamma function Γ(z) is a meromorphic function that extends the fac- torial n! to arbitrary complex values. For Re z > 0, we can find the gamma function by the integral: ∞ Γ(z)= e−ttz−1dt, Re z > 0. Z0 1 To see the relation with the factorial, we integrate by parts: ∞ Γ(z +1) = e−ttzdt Z0 ∞ z −t ∞ −t z−1 = −t e |0 + z e t dt Z0 = zΓ(z). ∞ −t This holds whenever Re z > 0. -
The Zeta Function and Its Relation to the Prime Number Theorem
THE ZETA FUNCTION AND ITS RELATION TO THE PRIME NUMBER THEOREM BEN RIFFER-REINERT Abstract. The zeta function is an important function in mathe- matics. In this paper, I will demonstrate an important fact about the zeros of the zeta function, and how it relates to the prime number theorem. Contents 1. Importance of the Zeta Function 1 2. Trivial Zeros 4 3. Important Observations 5 4. Zeros on Re(z)=1 7 5. Estimating 1/ζ and ζ0 8 6. The Function 9 7. Acknowledgements 12 References 12 1. Importance of the Zeta Function The Zeta function is a very important function in mathematics. While it was not created by Riemann, it is named after him because he was able to prove an important relationship between its zeros and the distribution of the prime numbers. His result is critical to the proof of the prime number theorem. There are several functions that will be used frequently throughout this paper. They are defined below. Definition 1.1. We define the Riemann zeta funtion as 1 X 1 ζ(z) = nz n=1 when jzj ≥ 1: 1 2 BEN RIFFER-REINERT Definition 1.2. We define the gamma function as Z 1 Γ(z) = e−ttz−1dt 0 over the complex plane. Definition 1.3. We define the xi function for all z with Re(z) > 1 as ξ(z) = π−s=2Γ(s=2)ζ(s): 1 P Lemma 1.1. Suppose fang is a series. If an < 1; then the product n=1 1 Q (1 + an) converges. Further, the product converges to 0 if and only n=1 if one if its factors is 0. -
8. Riemann's Plan for Proving the Prime Number Theorem
8. RIEMANN'S PLAN FOR PROVING THE PRIME NUMBER THEOREM 8.1. A method to accurately estimate the number of primes. Up to the middle of the nineteenth century, every approach to estimating ¼(x) = #fprimes · xg was relatively direct, based upon elementary number theory and combinatorial principles, or the theory of quadratic forms. In 1859, however, the great geometer Riemann took up the challenge of counting the primes in a very di®erent way. He wrote just one paper that could be called \number theory," but that one short memoir had an impact that has lasted nearly a century and a half, and its ideas have de¯ned the subject we now call analytic number theory. Riemann's memoir described a surprising approach to the problem, an approach using the theory of complex analysis, which was at that time still very much a developing sub- ject.1 This new approach of Riemann seemed to stray far away from the realm in which the original problem lived. However, it has two key features: ² it is a potentially practical way to settle the question once and for all; ² it makes predictions that are similar, though not identical, to the Gauss prediction. Indeed it even suggests a secondary term to compensate for the overcount we saw in the data in the table in section 2.10. Riemann's method is the basis of our main proof of the prime number theorem, and we shall spend this chapter giving a leisurely introduction to the key ideas in it. Let us begin by extracting the key prediction from Riemann's memoir and restating it in entirely elementary language: lcm[1; 2; 3; ¢ ¢ ¢ ; x] is about ex: Using data to test its accuracy we obtain: Nearest integer to x ln(lcm[1; 2; 3; ¢ ¢ ¢ ; x]) Di®erence 100 94 -6 1000 997 -3 10000 10013 13 100000 100052 57 1000000 999587 -413 Riemann's prediction can be expressed precisely and explicitly as p (8.1.1) j log(lcm[1; 2; ¢ ¢ ¢ ; x]) ¡ xj · 2 x(log x)2 for all x ¸ 100: 1Indeed, Riemann's memoir on this number-theoretic problem was a signi¯cant factor in the develop- ment of the theory of analytic functions, notably their global aspects.