A Method Using Photon Collapse and Entanglement to Transmit Information

TL;DR

This paper explores quantum wave function collapse and entanglement to develop a novel method for direct information transmission, challenging traditional views on entropy and eigenstate selection.

Contribution

It introduces a new approach leveraging photon collapse and entanglement for quantum information transfer, with insights into controlling quantum eigenstates.

Findings

Entropy can decrease in single-qubit systems, contrary to traditional laws.

Quantum eigenstates may be deliberately controlled rather than randomly chosen.

A new method for quantum information transmission using photon collapse and entanglement.

Abstract

Measurements cause quantum wave functions to collapse. In tackling this elusive issue, we embark on the exploration of entropy exhibited by single-qubit quantum systems. Our findings surprisingly challenge the conventional law of entropy never diminishing. We then interpret the confusing retrocausality phenomenon in Wheeler's delayed-choice experiments. The entropy reduction and the quantum retrocausality can be combined to investigate how measurements lead to collapse - A close link is shown between quantum wave function collapse and the ubiquity of photons in the environments. Next, by studying the overlooked phenomena of quantum wave function collapse, we find that quantum eigenstate sets may be artificially controlled rather than randomly selected. Our study uncovers an often overlooked aspect of quantum wave function collapse - a potential avenue for deliberate manipulation of quantum eigenstate sets, deviating from the conventional notion of random selection. Leveraging this novel insight, we propose an innovative method for direct information transmission utilizing photon wave function collapse and entanglement. Given the lack of efficient approaches for employing quantum mechanisms in information transfer, our research aims to push the boundaries of quantum mechanics and contribute to advancing this field.