#numbertheory — Public Fediverse posts

I’ve just posted on ResearchGate an annotated, step-by-step source edition of my zero-density paper. It reproduces the original passages unchanged, together with detailed explanations, dependency maps, and a guided proof chain.

I’m also close to completing a Lean formalization produced entirely by AI, with me supervising, checking, and directing the process. Progress is still slow because I’m doing this independently, with personal resources, without agents or institutional support. If anyone interested in Lean or analytic number theory would like to help, I’d be delighted to share everything, collaborate openly, and publish the formalization together, with shared credit and co-authorship for meaningful contributions.

To me, the main interest is not the numerical improvement over Guth-Maynard, but the technique behind it: centered Gram/spectral structure, additive energy, and exact physical synthesis, achieved without exceptional computational resources.

These ideas may be worth exploring beyond zero-density estimates, e.g. in functional and approximation theory, moment problems, harmonic/spectral analysis, PDEs, and mathematical physics.

I’m not a trillion-dollar institution, just an independent person who loves mathematics and science. I hope this project can be a small example of the democratization of mathematical knowledge.

Collaborators very welcome.

Paper "Proof Chain for the 24000/10451 Zero-Density Bound (Friendly Version)":
https://doi.org/10.13140/RG.2.2.11136.60161

#NumberTheory #RiemannZeta #Lean4 #AI #Formalization #OpenScience

I’ve just posted on ResearchGate an annotated, step-by-step source edition of my zero-density paper. It reproduces the original passages unchanged, together with detailed explanations, dependency maps, and a guided proof chain.

I’m also close to completing a Lean formalization produced entirely by AI, with me supervising, checking, and directing the process. Progress is still slow because I’m doing this independently, with personal resources, without agents or institutional support. If anyone interested in Lean or analytic number theory would like to help, I’d be delighted to share everything, collaborate openly, and publish the formalization together, with shared credit and co-authorship for meaningful contributions.

To me, the main interest is not the numerical improvement over Guth-Maynard, but the technique behind it: centered Gram/spectral structure, additive energy, and exact physical synthesis, achieved without exceptional computational resources.

These ideas may be worth exploring beyond zero-density estimates, e.g. in functional and approximation theory, moment problems, harmonic/spectral analysis, PDEs, and mathematical physics.

I’m not a trillion-dollar institution, just an independent person who loves mathematics and science. I hope this project can be a small example of the democratization of mathematical knowledge.

Collaborators very welcome.

Paper "Proof Chain for the 24000/10451 Zero-Density Bound (Friendly Version)":
https://doi.org/10.13140/RG.2.2.11136.60161

#NumberTheory #RiemannZeta #Lean4 #AI #Formalization #OpenScience

I’ve just posted on ResearchGate an annotated, step-by-step source edition of my zero-density paper. It reproduces the original passages unchanged, together with detailed explanations, dependency maps, and a guided proof chain.

I’m also close to completing a Lean formalization produced entirely by AI, with me supervising, checking, and directing the process. Progress is still slow because I’m doing this independently, with personal resources, without agents or institutional support. If anyone interested in Lean or analytic number theory would like to help, I’d be delighted to share everything, collaborate openly, and publish the formalization together, with shared credit and co-authorship for meaningful contributions.

To me, the main interest is not the numerical improvement over Guth-Maynard, but the technique behind it: centered Gram/spectral structure, additive energy, and exact physical synthesis, achieved without exceptional computational resources.

These ideas may be worth exploring beyond zero-density estimates, e.g. in functional and approximation theory, moment problems, harmonic/spectral analysis, PDEs, and mathematical physics.

I’m not a trillion-dollar institution, just an independent person who loves mathematics and science. I hope this project can be a small example of the democratization of mathematical knowledge.

Collaborators very welcome.

Paper "Proof Chain for the 24000/10451 Zero-Density Bound (Friendly Version)":
https://doi.org/10.13140/RG.2.2.11136.60161

#NumberTheory #RiemannZeta #Lean4 #AI #Formalization #OpenScience

I’ve just posted on ResearchGate an annotated, step-by-step source edition of my zero-density paper. It reproduces the original passages unchanged, together with detailed explanations, dependency maps, and a guided proof chain.

I’m also close to completing a Lean formalization produced entirely by AI, with me supervising, checking, and directing the process. Progress is still slow because I’m doing this independently, with personal resources, without agents or institutional support. If anyone interested in Lean or analytic number theory would like to help, I’d be delighted to share everything, collaborate openly, and publish the formalization together, with shared credit and co-authorship for meaningful contributions.

To me, the main interest is not the numerical improvement over Guth-Maynard, but the technique behind it: centered Gram/spectral structure, additive energy, and exact physical synthesis, achieved without exceptional computational resources.

These ideas may be worth exploring beyond zero-density estimates, e.g. in functional and approximation theory, moment problems, harmonic/spectral analysis, PDEs, and mathematical physics.

I’m not a trillion-dollar institution, just an independent person who loves mathematics and science. I hope this project can be a small example of the democratization of mathematical knowledge.

Collaborators very welcome.

Paper "Proof Chain for the 24000/10451 Zero-Density Bound (Friendly Version)":
https://doi.org/10.13140/RG.2.2.11136.60161

#NumberTheory #RiemannZeta #Lean4 #AI #Formalization #OpenScience

I’ve just posted on ResearchGate an annotated, step-by-step source edition of my zero-density paper. It reproduces the original passages unchanged, together with detailed explanations, dependency maps, and a guided proof chain.

I’m also close to completing a Lean formalization produced entirely by AI, with me supervising, checking, and directing the process. Progress is still slow because I’m doing this independently, with personal resources, without agents or institutional support. If anyone interested in Lean or analytic number theory would like to help, I’d be delighted to share everything, collaborate openly, and publish the formalization together, with shared credit and co-authorship for meaningful contributions.

To me, the main interest is not the numerical improvement over Guth-Maynard, but the technique behind it: centered Gram/spectral structure, additive energy, and exact physical synthesis, achieved without exceptional computational resources.

These ideas may be worth exploring beyond zero-density estimates, e.g. in functional and approximation theory, moment problems, harmonic/spectral analysis, PDEs, and mathematical physics.

I’m not a trillion-dollar institution, just an independent person who loves mathematics and science. I hope this project can be a small example of the democratization of mathematical knowledge.

Collaborators very welcome.

Paper "Proof Chain for the 24000/10451 Zero-Density Bound (Friendly Version)":
https://doi.org/10.13140/RG.2.2.11136.60161

#NumberTheory #RiemannZeta #Lean4 #AI #Formalization #OpenScience

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra

GTP-6 Astra: pedagogical report for Graduate / researcher new to the decompwlj: from Gaps to Divisor Geometry
https://decompwlj.com/GPT_Astra_decompwlj_graduate_report_2026-09-11.html

#decompwlj #math #NumberTheory #AI #report #PrimeNumbers #GPT6 #Astra