# quantum mechanics Published articles for quantum mechanics. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## GPT-5.2 derives a new result in theoretical physics DevFeed: [GPT-5.2 derives a new result in theoretical physics]() Original publisher: [Read original article]() Published: 2026-02-13T11:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [AI Chat]() Tags: [gpt](), [openai](), [particle-physics](), [physics](), [publication](), [quantum-mechanics](), [research]() ### AI overview GPT-5.2 proposed a formula for a gluon scattering amplitude in a specific half-collinear momentum regime. The article says the result was later proved and verified in a new preprint. ### Source excerpt A new preprint shows GPT-5.2 proposing a new formula for a gluon amplitude, later formally proved and verified by OpenAI and academic collaborators. ## A new quantum toolkit for optimization DevFeed: [A new quantum toolkit for optimization]() Original publisher: [Read original article]() Published: 2025-11-13T07:27:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Optimization](), [Quantum Computing](), [Programming](), [Algorithms & Theory](), [quantum mechanics](), [Google]() Tags: [algorithms](), [algorithms-theory](), [google](), [lattice](), [optimization](), [quantum](), [quantum-computing](), [quantum-mechanics]() ### AI overview Google Quantum AI researchers describe Decoded Quantum Interferometry, a quantum algorithm designed to find near-optimal solutions for certain optimization problems that are difficult for classical computers. The approach uses interference from quantum mechanics and depends on solving related lattice decoding problems. ### Source excerpt Algorithms & Theory ## God writes Haskell DevFeed: [God writes Haskell]() Original publisher: [Read original article]() Published: 2023-06-02T22:00:00Z Content type: opinion Language: en Sources: [Dennis Felsing]() Topics: [Haskell](), [quantum mechanics](), [Programming](), [Compiler](), [Data structures]() Tags: [arrays](), [compiler](), [haskell](), [memory-leak](), [programming](), [quantum](), [quantum-mechanics](), [type-system]() ### AI overview A humorous commentary compares Haskell concepts--including lazy evaluation, immutability, linked lists, type checking, and memory retention--to ideas from quantum mechanics and the physical universe. ### Source excerpt God famously does not play dice with the universe, but he seems to enjoy writing Haskell: Consider the wave-particle duality in quantum mechanics. Every particle behaves as a wave, as long as you haven't interacted with it. Thanks to Haskell's lazy evaluation values are also only evaluated once they are accessed (interacted with particles), and stay unevaluated thunks (waves) in the meantime. Two particles can be Quantum-entangled, so that their states depend on each other, even though the particles are seperated by any distance. In Haskell a value, whether it's evaluated yet or not, can also be shared and then used in a totally different location in the program without having to copy it. The value is even immutable, so that you can't change it from one location and thus influence the other. Similarly for entangled particles you can't manipulate one to change the state of the other particle, which might be far away and thus break the maximum speed of information. Since values are immutable they have to be cleaned up more often in Haskell than typically in imperative languages. GHC, the most commonly used Haskell compiler, allocates new data in a special area. Only after a supernova will the still-relevant data be ejected into the larger universe. Haskell beginners often use lists instead of arrays. You can't do random access in a linked list, but only access the first element and then the rest of the list. The real world also doesn't allow you random access, you are limited by the speed of light and have to go from one location to the next. Time also seems to be a linked list, not even doubly linked, since you can't go back after accessing the current element. Seems like an awkward bug. Since the Haskell type system is so good at catching bugs, you often feel like you don't even need to write tests. This is unfortunately untrue, as the strange physical bugs of our universe demonstrate: The speed of light happens to stay the same, no matter what speed you move at. Th ## The Quantum Bit DevFeed: [The Quantum Bit]() Original publisher: [Read original article]() Published: 2014-12-15T10:00:52Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Quantum Computing](), [Computing](), [circuit]() Tags: [bits](), [circuit](), [circuits](), [complex-numbers](), [computing](), [linear-algebra](), [mathematics](), [measurement](), [quantum](), [quantum-computing](), [quantum-mechanics](), [qubit](), [unitary-matrices]() ### AI overview An introduction to quantum computing that extends classical circuit concepts to qubits. It defines a qubit as a unit vector in the complex plane of two dimensions and explains why extracting information from qubits differs from reading classical bits. ### Source excerpt The best place to start our journey through quantum computing is to recall how classical computing works and try to extend it. Since our final quantum computing model will be a circuit model, we should informally discuss circuits first. A circuit has three parts: the "inputs," which are bits (either zero or one); the "gates," which represent the lowest-level computations we perform on bits; and the "wires," which connect the outputs of gates to the inputs of other gates. ## A Motivation for Quantum Computing DevFeed: [A Motivation for Quantum Computing]() Original publisher: [Read original article]() Published: 2014-12-08T10:00:48Z Content type: article Language: en Sources: [Jeremy Kun]() Topics: [Quantum Computing](), [circuit](), [Computing](), [quantum mechanics]() Tags: [circuit](), [computing](), [experiments](), [mathematics](), [physics](), [quantum](), [quantum-computing](), [quantum-mechanics](), [unitary-matrices]() ### AI overview This article motivates the study of quantum computing by connecting quantum mechanics with the quantum circuit, a computing model that extends the classical Turing-machine perspective. It argues for teaching quantum mechanics from its conceptual core, including amplitudes and generalized probability. ### Source excerpt Quantum mechanics is one of the leading scientific theories describing the rules that govern the universe. It's discovery and formulation was one of the most important revolutions in the history of mankind, contributing in no small part to the invention of the transistor and the laser. Here at Math ∩ Programming we don't put too much emphasis on physics or engineering, so it might seem curious to study quantum physics. But as the reader is likely aware, quantum mechanics forms the basis of one of the most interesting models of computing since the Turing machine: the quantum circuit.