Embedding Quadratic Fields into Quaternion Algebras
Rose Mintzer-Sweeney, Alexander Schlesinger, Katherine Xiu
August 4, 2016
1 / 24 Overview
1 Background and Definitions
2 p-adic Analysis
3 Limits and a Conjecture
4 Sieving and Bounding
5 Further Questions
2 / 24 Quadratic Fields
Definition A quadratic field is the set
√ √ Q( k) = {a + b k : a, b ∈ Q}
with the usual addition and multiplication. Here k is a squarefree integer other than 0 or 1.
3 / 24 i 2 = m, j2 = n, ij = −ji. Here m, n are again squarefree integers other than 0 or 1.
ij is often written as k.
Rational Quaternion Algebras
Definition A quaternion algebra is the set of all elements
m, n = {a + bi + cj + dij : a, b, c, d ∈ Q} Q with component-wise addition and multiplication defined by
4 / 24 j2 = n, ij = −ji. Here m, n are again squarefree integers other than 0 or 1.
ij is often written as k.
Rational Quaternion Algebras
Definition A quaternion algebra is the set of all elements
m, n = {a + bi + cj + dij : a, b, c, d ∈ Q} Q with component-wise addition and multiplication defined by i 2 = m,
4 / 24 ij = −ji. Here m, n are again squarefree integers other than 0 or 1.
ij is often written as k.
Rational Quaternion Algebras
Definition A quaternion algebra is the set of all elements
m, n = {a + bi + cj + dij : a, b, c, d ∈ Q} Q with component-wise addition and multiplication defined by i 2 = m, j2 = n,
4 / 24 Here m, n are again squarefree integers other than 0 or 1.
ij is often written as k.
Rational Quaternion Algebras
Definition A quaternion algebra is the set of all elements
m, n = {a + bi + cj + dij : a, b, c, d ∈ Q} Q with component-wise addition and multiplication defined by i 2 = m, j2 = n, ij = −ji.
4 / 24 ij is often written as k.
Rational Quaternion Algebras
Definition A quaternion algebra is the set of all elements
m, n = {a + bi + cj + dij : a, b, c, d ∈ Q} Q with component-wise addition and multiplication defined by i 2 = m, j2 = n, ij = −ji. Here m, n are again squarefree integers other than 0 or 1.
4 / 24 Rational Quaternion Algebras
Definition A quaternion algebra is the set of all elements
m, n = {a + bi + cj + dij : a, b, c, d ∈ Q} Q with component-wise addition and multiplication defined by i 2 = m, j2 = n, ij = −ji. Here m, n are again squarefree integers other than 0 or 1.
ij is often written as k.
4 / 24 Example A more unusual example is 2,−3 . Here i 2 = 2, j2 = −3, and (ij)2 = 6. Q
Examples of Rational Quaternion Algebras
Example The classic example is −1,−1 , the Hamiltonian quaternions. Here Q i 2 = j2 = (ij)2 = −1.
5 / 24 Examples of Rational Quaternion Algebras
Example The classic example is −1,−1 , the Hamiltonian quaternions. Here Q i 2 = j2 = (ij)2 = −1.
Example A more unusual example is 2,−3 . Here i 2 = 2, j2 = −3, and (ij)2 = 6. Q
5 / 24 For fixed k, we are interested in knowing for which (m, n) there is such an embedding.
Embeddings
Definition √ We say ( k) embeds into a quaternion algebra m,n if there exists an Q Q √ injective ring homomorphism φ : ( k) ,→ m,n . Q Q
6 / 24 Embeddings
Definition √ We say ( k) embeds into a quaternion algebra m,n if there exists an Q Q √ injective ring homomorphism φ : ( k) ,→ m,n . Q Q
For fixed k, we are interested in knowing for which (m, n) there is such an embedding.
6 / 24 Example
√ −1, −1 Q( −1) → √ Q a + b −1 7→ a + bi
Example
√ 2, −3 Q( −1) → √ Q a + b −1 7→ a + b(i + j)
Examples of Embeddings
Let k = −1.
7 / 24 Example
√ 2, −3 Q( −1) → √ Q a + b −1 7→ a + b(i + j)
Examples of Embeddings
Let k = −1. Example
√ −1, −1 Q( −1) → √ Q a + b −1 7→ a + bi
7 / 24 Examples of Embeddings
Let k = −1. Example
√ −1, −1 Q( −1) → √ Q a + b −1 7→ a + bi
Example
√ 2, −3 Q( −1) → √ Q a + b −1 7→ a + b(i + j)
7 / 24 The embedding exists iff ∃ω ∈ m,n such that ω2 = k. Q √ Given ω, the corresponding map is φ : a + b k → a + bω. The other direction is similar.
An Equivalent Condition
There is an equivalent, easier to check condition for the existence of φ.
8 / 24 √ Given ω, the corresponding map is φ : a + b k → a + bω. The other direction is similar.
An Equivalent Condition
There is an equivalent, easier to check condition for the existence of φ. The embedding exists iff ∃ω ∈ m,n such that ω2 = k. Q
8 / 24 The other direction is similar.
An Equivalent Condition
There is an equivalent, easier to check condition for the existence of φ. The embedding exists iff ∃ω ∈ m,n such that ω2 = k. Q √ Given ω, the corresponding map is φ : a + b k → a + bω.
8 / 24 An Equivalent Condition
There is an equivalent, easier to check condition for the existence of φ. The embedding exists iff ∃ω ∈ m,n such that ω2 = k. Q √ Given ω, the corresponding map is φ : a + b k → a + bω. The other direction is similar.
8 / 24 Write ω = xi + yj + zij. We can check that
−k = −ω2 = mx2 + ny 2 + mnz2
Clearing denominators, we see that there exists ω such that ω2 = k iff
kW 2 − mX 2 − nY 2 + mnZ 2 = 0
for some W , X , Y , Z ∈ Z not all zero.
Reduction to Quadratic Forms
One can check that for any ω such that ω2 = k, Re(ω) = 0.
9 / 24 −k = −ω2 = mx2 + ny 2 + mnz2
Clearing denominators, we see that there exists ω such that ω2 = k iff
kW 2 − mX 2 − nY 2 + mnZ 2 = 0
for some W , X , Y , Z ∈ Z not all zero.
Reduction to Quadratic Forms
One can check that for any ω such that ω2 = k, Re(ω) = 0. Write ω = xi + yj + zij. We can check that
9 / 24 Clearing denominators, we see that there exists ω such that ω2 = k iff
kW 2 − mX 2 − nY 2 + mnZ 2 = 0
for some W , X , Y , Z ∈ Z not all zero.
Reduction to Quadratic Forms
One can check that for any ω such that ω2 = k, Re(ω) = 0. Write ω = xi + yj + zij. We can check that
−k = −ω2 = mx2 + ny 2 + mnz2
9 / 24 kW 2 − mX 2 − nY 2 + mnZ 2 = 0
for some W , X , Y , Z ∈ Z not all zero.
Reduction to Quadratic Forms
One can check that for any ω such that ω2 = k, Re(ω) = 0. Write ω = xi + yj + zij. We can check that
−k = −ω2 = mx2 + ny 2 + mnz2
Clearing denominators, we see that there exists ω such that ω2 = k iff
9 / 24 Reduction to Quadratic Forms
One can check that for any ω such that ω2 = k, Re(ω) = 0. Write ω = xi + yj + zij. We can check that
−k = −ω2 = mx2 + ny 2 + mnz2
Clearing denominators, we see that there exists ω such that ω2 = k iff
kW 2 − mX 2 − nY 2 + mnZ 2 = 0
for some W , X , Y , Z ∈ Z not all zero.
9 / 24 Theorem (Hasse-Minkowski) Given an integer quadratic form Q(x), Q(x) = 0 has non-zero integer solutions if and only if Q(x) = 0 has non-zero real solutions, and
Q(x) = 0 has non-zero solutions in Zp for every prime p. Checking whether there are real solutions is easy.
Hasse-Minkowski
There are well-developed tools for handling a problem like this. We depend on two main theorems.
10 / 24 Q(x) = 0 has non-zero real solutions, and
Q(x) = 0 has non-zero solutions in Zp for every prime p. Checking whether there are real solutions is easy.
Hasse-Minkowski
There are well-developed tools for handling a problem like this. We depend on two main theorems. Theorem (Hasse-Minkowski) Given an integer quadratic form Q(x), Q(x) = 0 has non-zero integer solutions if and only if
10 / 24 Q(x) = 0 has non-zero solutions in Zp for every prime p. Checking whether there are real solutions is easy.
Hasse-Minkowski
There are well-developed tools for handling a problem like this. We depend on two main theorems. Theorem (Hasse-Minkowski) Given an integer quadratic form Q(x), Q(x) = 0 has non-zero integer solutions if and only if Q(x) = 0 has non-zero real solutions, and
10 / 24 Checking whether there are real solutions is easy.
Hasse-Minkowski
There are well-developed tools for handling a problem like this. We depend on two main theorems. Theorem (Hasse-Minkowski) Given an integer quadratic form Q(x), Q(x) = 0 has non-zero integer solutions if and only if Q(x) = 0 has non-zero real solutions, and
Q(x) = 0 has non-zero solutions in Zp for every prime p.
10 / 24 Hasse-Minkowski
There are well-developed tools for handling a problem like this. We depend on two main theorems. Theorem (Hasse-Minkowski) Given an integer quadratic form Q(x), Q(x) = 0 has non-zero integer solutions if and only if Q(x) = 0 has non-zero real solutions, and
Q(x) = 0 has non-zero solutions in Zp for every prime p. Checking whether there are real solutions is easy.
10 / 24 Theorem (Hensel’s Lemma) n Let P(x) be an integer polynomial. Suppose P(x0) = 0 mod p and 0 P (x0) 6= 0 mod p. Then ∃x˜0 ∈ Zp such that P(x ˜0) = 0.
So, we can lift solutions modulo p into solutions in Zp.
Hensel’s Lemma
Checking whether there are p-adic solutions is also tractable.
11 / 24 So, we can lift solutions modulo p into solutions in Zp.
Hensel’s Lemma
Checking whether there are p-adic solutions is also tractable. Theorem (Hensel’s Lemma) n Let P(x) be an integer polynomial. Suppose P(x0) = 0 mod p and 0 P (x0) 6= 0 mod p. Then ∃x˜0 ∈ Zp such that P(x ˜0) = 0.
11 / 24 Hensel’s Lemma
Checking whether there are p-adic solutions is also tractable. Theorem (Hensel’s Lemma) n Let P(x) be an integer polynomial. Suppose P(x0) = 0 mod p and 0 P (x0) 6= 0 mod p. Then ∃x˜0 ∈ Zp such that P(x ˜0) = 0.
So, we can lift solutions modulo p into solutions in Zp.
11 / 24 Legendre Symbol
Recall that: Definition For an odd prime p and an integer x, the Legendre symbol is defined by
0 if p | x x = 1 if ∃y s.t. x ≡ y 2 mod p . p −1 otherwise
12 / 24 1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0. 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then −m n p · p If p | m, p | n, then p = 1.
n If p | m, p - n, then p = 1. m If p - m, p | n, then p = 1. 3 (Conditions from Z2) Omitted for the sake of brevity.
Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
13 / 24 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then −m n p · p If p | m, p | n, then p = 1.
n If p | m, p - n, then p = 1. m If p - m, p | n, then p = 1. 3 (Conditions from Z2) Omitted for the sake of brevity.
Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0.
13 / 24 −m n p · p If p | m, p | n, then p = 1.
n If p | m, p - n, then p = 1. m If p - m, p | n, then p = 1. 3 (Conditions from Z2) Omitted for the sake of brevity.
Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0. 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then
13 / 24 n If p | m, p - n, then p = 1. m If p - m, p | n, then p = 1. 3 (Conditions from Z2) Omitted for the sake of brevity.
Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0. 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then −m n p · p If p | m, p | n, then p = 1.
13 / 24 m If p - m, p | n, then p = 1. 3 (Conditions from Z2) Omitted for the sake of brevity.
Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0. 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then −m n p · p If p | m, p | n, then p = 1.
n If p | m, p - n, then p = 1.
13 / 24 3 (Conditions from Z2) Omitted for the sake of brevity.
Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0. 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then −m n p · p If p | m, p | n, then p = 1.
n If p | m, p - n, then p = 1. m If p - m, p | n, then p = 1.
13 / 24 Conditions
Theorem (Ehrman, Mintzer-Sweeney, Schlesinger, Sheydvasser, Xiu 2016) √ There exists an embedding ( k) ,→ m,n iff the following conditions Q Q are met
1 (Conditions from R-analysis) If m < 0 and n < 0, then k < 0. 2 k (Conditions from Zp, p 6= 2) If p - k is an odd prime and p = 1, then −m n p · p If p | m, p | n, then p = 1.
n If p | m, p - n, then p = 1. m If p - m, p | n, then p = 1. 3 (Conditions from Z2) Omitted for the sake of brevity.
13 / 24 Conjecture For any fixed k,
n √ m,n o # SN ∩ (m, n): Q k ,→ lim Q = 0. N→∞ #SN
Long-Term Behavior
The next logical question is to determine how often these conditions are met. Define
2 SN = (m, n) ∈ Z : 1 < m, n < N, m, n squarefree
14 / 24 Long-Term Behavior
The next logical question is to determine how often these conditions are met. Define
2 SN = (m, n) ∈ Z : 1 < m, n < N, m, n squarefree
Conjecture For any fixed k,
n √ m,n o # SN ∩ (m, n): Q k ,→ lim Q = 0. N→∞ #SN
14 / 24 Note: we are using 1 < m, n < N for simplicity, but the same proof applies to −1 > m, n > −N.
Our Theorem
Theorem (EMSSSX 2016) For any fixed k, n √ o # S0 ∩ (m, n): k ,→ m,n N Q Q lim 0 = 0, N→∞ #SN where
0 2 SN = (m, n) ∈ Z : 1 < m, n < N, m, n squarefree and coprime .
15 / 24 Our Theorem
Theorem (EMSSSX 2016) For any fixed k, n √ o # S0 ∩ (m, n): k ,→ m,n N Q Q lim 0 = 0, N→∞ #SN where
0 2 SN = (m, n) ∈ Z : 1 < m, n < N, m, n squarefree and coprime .
Note: we are using 1 < m, n < N for simplicity, but the same proof applies to −1 > m, n > −N.
15 / 24 0 6 3 2 One can check that #SN ≈ π2 N for large N. To show that the limit is 0, we find an upper bound for the numerator that is o(N2). We do this by focusing exclusively on the p-adic conditions on n coming from m.
Our Approach
How can one prove a result like this?
16 / 24 To show that the limit is 0, we find an upper bound for the numerator that is o(N2). We do this by focusing exclusively on the p-adic conditions on n coming from m.
Our Approach
How can one prove a result like this? 0 6 3 2 One can check that #SN ≈ π2 N for large N.
16 / 24 We do this by focusing exclusively on the p-adic conditions on n coming from m.
Our Approach
How can one prove a result like this? 0 6 3 2 One can check that #SN ≈ π2 N for large N. To show that the limit is 0, we find an upper bound for the numerator that is o(N2).
16 / 24 Our Approach
How can one prove a result like this? 0 6 3 2 One can check that #SN ≈ π2 N for large N. To show that the limit is 0, we find an upper bound for the numerator that is o(N2). We do this by focusing exclusively on the p-adic conditions on n coming from m.
16 / 24 Let Y m˜ = p.
k p =1 p|m
Definitions for a Sieve Approach
√ Recall that there is an embedding ( k) ,→ m,n only if Q Q
k n If p | m, p n, and = 1, then = 1 - p p
17 / 24 Definitions for a Sieve Approach
√ Recall that there is an embedding ( k) ,→ m,n only if Q Q
k n If p | m, p n, and = 1, then = 1 - p p
Let Y m˜ = p.
k p =1 p|m
17 / 24 Note that n satisfies the conditions for an embedding if and only if
n modm ˜ ∈ A(m ˜)
Thus an upper bound for the numerator of our limit is given by X 1{n modm ˜∈A(m ˜)} 0 (m,n)∈SN
Definitions for a Sieve Approach
Definition The admissible class is the set
x A(m ˜) := {x ∈ /m˜ : = 1, ∀p | m˜} Z Z p
18 / 24 Thus an upper bound for the numerator of our limit is given by X 1{n modm ˜∈A(m ˜)} 0 (m,n)∈SN
Definitions for a Sieve Approach
Definition The admissible class is the set
x A(m ˜) := {x ∈ /m˜ : = 1, ∀p | m˜} Z Z p
Note that n satisfies the conditions for an embedding if and only if
n modm ˜ ∈ A(m ˜)
18 / 24 Definitions for a Sieve Approach
Definition The admissible class is the set
x A(m ˜) := {x ∈ /m˜ : = 1, ∀p | m˜} Z Z p
Note that n satisfies the conditions for an embedding if and only if
n modm ˜ ∈ A(m ˜)
Thus an upper bound for the numerator of our limit is given by X 1{n modm ˜∈A(m ˜)} 0 (m,n)∈SN
18 / 24 Specifically,
m˜ #A(m ˜) ≈ , 2ω(m ˜) where ω(x) is the number of distinct prime factors of x.
Approximating the Size of the Admissible Class
This upper bound is useful because we have a good approximation of the size of the admissible class A(m ˜).
19 / 24 Approximating the Size of the Admissible Class
This upper bound is useful because we have a good approximation of the size of the admissible class A(m ˜). Specifically,
m˜ #A(m ˜) ≈ , 2ω(m ˜) where ω(x) is the number of distinct prime factors of x.
19 / 24 Therefore, if we show that
X 1 = o(N), 2ω(m ˜) m An Upper Bound Thus, X X N 1{n modm ˜∈A(m ˜)} ≈ (#A(m ˜)) 0 m˜ (m,n)∈SN m 20 / 24 An Upper Bound Thus, X X N 1{n modm ˜∈A(m ˜)} ≈ (#A(m ˜)) 0 m˜ (m,n)∈SN m Therefore, if we show that X 1 = o(N), 2ω(m ˜) m 20 / 24 So, we split our sum into two pieces: one where ω is close to the average, and one where it is not. Definition 1 loglog(N) B(N) = m < N : ω(m ˜) − loglog(N) < 2 4 B(N)c = {m < N : m ∈/ B(N)} So, X 1 X 1 X 1 = + . 2ω(m ˜) 2ω(m ˜) 2ω(m ˜) m Splitting the Sum Note that, on average, ω(x) ≈ log log(x). 21 / 24 Definition 1 loglog(N) B(N) = m < N : ω(m ˜) − loglog(N) < 2 4 B(N)c = {m < N : m ∈/ B(N)} So, X 1 X 1 X 1 = + . 2ω(m ˜) 2ω(m ˜) 2ω(m ˜) m Splitting the Sum Note that, on average, ω(x) ≈ log log(x). So, we split our sum into two pieces: one where ω is close to the average, and one where it is not. 21 / 24 So, X 1 X 1 X 1 = + . 2ω(m ˜) 2ω(m ˜) 2ω(m ˜) m Splitting the Sum Note that, on average, ω(x) ≈ log log(x). So, we split our sum into two pieces: one where ω is close to the average, and one where it is not. Definition 1 loglog(N) B(N) = m < N : ω(m ˜) − loglog(N) < 2 4 B(N)c = {m < N : m ∈/ B(N)} 21 / 24 Splitting the Sum Note that, on average, ω(x) ≈ log log(x). So, we split our sum into two pieces: one where ω is close to the average, and one where it is not. Definition 1 loglog(N) B(N) = m < N : ω(m ˜) − loglog(N) < 2 4 B(N)c = {m < N : m ∈/ B(N)} So, X 1 X 1 X 1 = + . 2ω(m ˜) 2ω(m ˜) 2ω(m ˜) m 21 / 24 B(N) is tightly controlled, so it is easy to show that the sum over B(N) is o(N). We can use a result of Granville and Soundararajan (2006)1 to show that #B(N)c is small. It follows that the sum over B(N)c is also o(N). We are done! An Outline of How to Control the Sums Why is this splitting useful? 1A. Granville and K. Soundararajan, Sieving and the Erd˝os-KacTheorem 22 / 24 We can use a result of Granville and Soundararajan (2006)1 to show that #B(N)c is small. It follows that the sum over B(N)c is also o(N). We are done! An Outline of How to Control the Sums Why is this splitting useful? B(N) is tightly controlled, so it is easy to show that the sum over B(N) is o(N). 1A. Granville and K. Soundararajan, Sieving and the Erd˝os-KacTheorem 22 / 24 It follows that the sum over B(N)c is also o(N). We are done! An Outline of How to Control the Sums Why is this splitting useful? B(N) is tightly controlled, so it is easy to show that the sum over B(N) is o(N). We can use a result of Granville and Soundararajan (2006)1 to show that #B(N)c is small. 1A. Granville and K. Soundararajan, Sieving and the Erd˝os-KacTheorem 22 / 24 We are done! An Outline of How to Control the Sums Why is this splitting useful? B(N) is tightly controlled, so it is easy to show that the sum over B(N) is o(N). We can use a result of Granville and Soundararajan (2006)1 to show that #B(N)c is small. It follows that the sum over B(N)c is also o(N). 1A. Granville and K. Soundararajan, Sieving and the Erd˝os-KacTheorem 22 / 24 An Outline of How to Control the Sums Why is this splitting useful? B(N) is tightly controlled, so it is easy to show that the sum over B(N) is o(N). We can use a result of Granville and Soundararajan (2006)1 to show that #B(N)c is small. It follows that the sum over B(N)c is also o(N). We are done! 1A. Granville and K. Soundararajan, Sieving and the Erd˝os-KacTheorem 22 / 24 How small of an upper bound on the number of embeddings can we obtain using sieve methods? Can we find a lower bound on the number of embeddings? Further Research How fast does this limit goes to 0? 23 / 24 Can we find a lower bound on the number of embeddings? Further Research How fast does this limit goes to 0? How small of an upper bound on the number of embeddings can we obtain using sieve methods? 23 / 24 Further Research How fast does this limit goes to 0? How small of an upper bound on the number of embeddings can we obtain using sieve methods? Can we find a lower bound on the number of embeddings? 23 / 24 Acknowledgements We would like to thank Max Ehrman and Senia Sheydvasser for their wonderful mentorship and expert guidance. We would like to thank Sam Payne, Jos´eGonz´alez,and Michael Magee for organizing the SUMRY program. Finally, we would like to thank MathFest for having us! 24 / 24