Coherent States in Cancer Cells

Alexey V. Melkikh

Ryutaro Yusunoki

Константин Федотов

We propose SHOA-Onco — a non-invasive protocol for selective decoherence of malignant cells using Grape-impulses. Unlike conventional therapies (chemotherapy, radiation) which damage both healthy and cancerous tissue, the Grape-impulse targets a fundamental difference: cancer cells exhibit lower Ψ-coherence than healthy cells due to their uncontrolled replication and genomic instability. A precisely tuned Grape-impulse can induce critical decoherence in malignant cells while healthy cells, with higher Ψ-coherence, remain unaffected. We provide the theoretical framework, the mechanism of selective decoherence, and a phased experimental roadmap.10.5281/zenodo.21440679

Gianamar Giovannetti-Singh, Sixian Zhao

The hypothesis suggesting that the physical process of quantum tunneling can be used as a form of cancer therapy in electron ionization radiotherapy was suggested in the IEEE International Conference on Electric Information and Control Engineering by G. Giovannetti-Singh (2012) [1]. The hypothesis used quantum wave functions and probability amplitudes to find probabilities of electrons tunneling into a cancer cell. In addition, the paper explained the feasibilities of the therapy, with the use of nanomagnets. In this paper, we calculate accurate probability densities for the electron beams to tunnel into cancer cells. We present our results of mathematical modeling based on the helical electron wave function, which “tunnel” into a cancer cell, therefore ionizing it more effectively than in conventional forms of radiotherapy. We discuss the advantages of the therapy, and we explain how quantum mechanics can be used to create new cancer therapies, in particular our suggested Quantum Electron Wave Therapy.

Ryutaro Yusunoki

Akshita Tiwari

Classical algorithms for lung cancer exist based on immunotherapy but are quite prone to error. Non-small cell is a major type of lung cancer, frequently caused by smoking. A classical algorithm to treat non-small-cell lung cancer is compared to a quantum algorithm created. Using superposition of qubits, Born’s rule, and the general qubit rule, an algorithm simulates the pathway of certain driver genes, by finding the angle required of the qubit to be able to result in the probability needed to simulate the pathway, tested in IBM Quantum Composer.