Quantum Foundations and the Building Blocks of Matter

Dieter Suter

The interaction between matter and radiation has fascinated physicists for a long time. On the material side, the most detailed investigations of these processes concentrate on atoms, the basic constituents of matter. The radiation that is involved in these processes is primarily light, i.e., radiation whose wavelength is in the range of a few tenths of a micron to a few microns. Under today's laboratory conditions, this radiation is generally produced by a laser. This introduction outlines our picture of these constituents and presents some of the concepts and models that we will use throughout this book. Atoms Historical Early models: atoms as building blocks The term “atom” was coined by the Greek philosopher Democritus of Abdera (460–370 B.C.), who tried to reconcile change with eternal existence. His solution to this dilemma was that matter was not indefinitely divisible, but consisted of structureless building blocks that he called atoms. According to Democritus and other proponents of this idea, the diverse aspects of matter, as we know it, are a result of different arrangements of the same building blocks in empty space (Melsen 1957; Simonyi 1990). The most important opponent of this theory was Aristotle (384–322 B.C.), and his great influence is probably the main reason that the atomic hypothesis was not widely accepted, but lay dormant for two thousand years. It reappeared only in the eighteenth century, when the emerging experimental science found convincing evidence that matter does indeed consist of elementary building blocks.

Climério Paulo da Silva Neto

César Feniou

Quantum computing holds promise for addressing challenges in quantum chemistry. The foundational Quantum Phase Estimation (QPE) algorithm, established early on, remains the state-of-the-art for this field. However, there are considerable opportunities for refinement across its building blocks, spanning from the preparation of initial states to the circuit decomposition of general quantum oracles. In particular, bridging the gap between efficient classical pre-computation and asymptotically advantageous quantum post-processing seems to be a natural approach towards achieving an advantage during the early stages of fault-tolerant quantum computing

Alan V. Durrant

Timothy Zaklama, Daniele Guerci, Liang Fu

We present an attention-based foundation model architecture for learning and predicting quantum states across Hamiltonian parameters, system sizes, and physical systems. Using only basis configurations and physical parameters as inputs, our trained neural network is able to produce highly accurate ground state wavefunctions. For example, we build the phase diagram for the 2D square-lattice t t – V V model with N N particles, from only 18 training points in parameter space (V/t,N) ( V / t , N ) . Thus, our architecture provides a basis for building a universal foundation model for quantum matter.