Massachusetts Institute of Mathematics

Massachusetts Institute of Mathematics

We conducts basic and applied research of mathmatics and computer science. Our main research areas are algebra, artificial intelligence and quantum computing.

01

Algebra

Among mathematical structures, structures given as algebraic systems, such as groups, rings, and fields, are called algebraic structures. Algebraic structures include not only especially important ones such as groups, rings, and fields, but also Lie algebras, lattices, and so on. We are not only engaged in corporate activities, but also in academic research in pure mathematics, pursuing the rigor of the mathematics being discussed and the beauty of mathematics on its own, based on abstraction.

02

Artificial General Intelligence

Artificial General Intelligence (AGI), or general-purpose AI, is a theoretical form of AI in which a machine is as intelligent as a human. It has a self-aware consciousness with the ability to solve problems, learn, and plan for the future. Artificial super intelligence (ASI), also called superintelligence, is superior to the intelligence and capabilities of the human brain. We are conducting scientific research to create ASI/AGI by simulating the human brain at the atomic/molecular level.

03

Quantum Computing

A quantum computer is a computing system that uses the principles of quantum mechanics. It is theoretically fast and has the ability to compute solutions to problems that conventional Neumann-type computers are incapable of computing in practice due to insufficient capacity. The logic elements (bits) of ordinary computers are based on either of two states, 1 or 0. Quantum computers, however, use "superposition states" unique to quantum mechanics and are based on quantum elements (qubits, qbits, qbit) that can superimpose both 1 and 0 states. We are conducting scientific research on quantum computers as a world system to simulate and control all things in the universe.

Our Main Papers

1. A Categorical Framework: Bridging Number Theory, Geometry, and Analytic Number Theory

2. Categorical Prime Ideal

3. YuM-Theory: Hypothesis that elementary particles are 3-dimensional voxels

4. String Computer(Submitted to Physical Review Letters)

5. Unifying Individual Machine Learning Models through Group Theory(To be submitted to AAAI-25)

6. Unification of Individual Quantum Machine Learning Models: A Schrödinger Perspective(To be submitted to AAAI-25)

7. A Relativistic Approach to Artificial Intelligence: Bridging the Gap Between Spacetime and Neural Networks

(Submitted to Physical Review Letters )

8. Quantum Error Correction with ML

9. Whole-Brain Emulation through the Lens of the Schrödinger Equation(To be submitted to NeurIPS 2024)

10. Advancements in Algebraic K-Theory and Arithmetic Geometry An exploration through the lens of Number Theory

11. A Novel Neural Network Architecture Inspired by the Hodgkin-Huxley Equations From Currents to Computations

12. Improving Judicial Objectivity with Higher-order Polynomial Projection Operations (HiPPO)

Categorical Quantum Mechanics and FTQC

Article for 2030s

Categorical quantum mechanics and FTQC are two related topics that explore the foundations and applications of quantum computation using mathematical and computational tools.

Article for 2040s

The main question that this article aims to explore is whether AGI and M-Theory are compatible or incompatible, and what implications this has for the possibility of creating and understanding artificial intelligence with quantum gravity.