Quantum Abacus

In the paper's words

The scalability of active, gate-based quantum computers is fundamentally challenged by the “Thermodynamic Wall,” where the heat from control electronics becomes prohibitive. This study computationally investigates the “Quantum Abacus,” a passive quantum computing architecture that circumvents this limit by using static strain engineering to control fermionic transport. We introduce a theoretical framework that unifies the Signal-Worker ontology with the physics of strain-induced gauge fields and “Tensor Locking.” Using a 1D tight-binding model parameterized for the Weyl semimetal TaAs, we demonstrate that achievable strain gradients (0-5%) can form isolated quantum registers and modulate fermionic hopping integrals.

The abstract, verbatim, and its opening sentence is the claim. Every line below is quoted from the text.

Numbers it reports

1. The final state fidelity exceeds 99.9%, demonstrating that strain-mediated transport can be performed with quantum error rates below the threshold for fault tolerance.

   from 4.3 High-Fidelity Adiabatic

2. This enhanced sensitivity makes TaAs a more efficient and powerful substrate for strain-based control, allowing for robust operation even within the conservative 5% strain limits used in our simulations (Zhang et al., 2024).

   from 4.5 TaAs Specific Performance

3. Crucially, simulations utilizing optimized control pulses demonstrate coherent adiabatic transfer with fidelities exceeding 99.9%, resolving previous concerns regarding operation quality.

   from Abstract

4. The simulation, parameterized with a Grüneisen constant of $\beta=3.0$, demonstrates that a realistic 5% strain can suppress the hopping energy to approximately 86% of its equilibrium value.

   from 4.1 Hopping Integral

5. While less dramatic than the 20% strain scenarios often discussed in graphene nanobubbles, this modulation is sufficient to create effective potential barriers when integrated over a lattice, validating the feasibility of strain control within the fracture limits of bulk crystals (Zhang et al., 2024).

   from 4.1 Hopping Integral

How it is done

1. This approach replaces the dissipative electromagnetic driving of transmon gates with conservative elastic forces, offering a pathway to reversible computation that operates near the thermodynamic ground state.

   from 1.2 The Quantum Abacus Concept

2. This hierarchical approach posits that static structural control should form the foundation of quantum architecture, with dynamic fields reserved only for the fastest operations.

   from 1.4 The Superconducting

3. This ontological mapping transforms the passive substrate from a source of noise into a computational resource, where the geometry of the lattice encodes the algorithm itself.

   from 2.1 The Signal-Worker Ontology

4. Protocol The simulation of the strain landscape requires mapping continuous strain tensor fields onto the discrete lattice grid.

   from 3.2 Strain Tensor Simulation

What would falsify it

The paper's text states no explicit falsification criterion; the limits below are what it says about where the claim stops.

Where the claim stops

1. However, the precision required to engineer these fields demands a rigorous understanding of the strain-response tensor.

   from 1.3 Strain as a Gauge Field

2. However, integrating these complex crystals with piezoelectric actuators presents significant fabrication challenges.

   from 1.5 Material Platforms:

3. The Signal-Worker framework, however, posits that the environment is a programmable “Signal”—a collective bosonic field—that dictates the dynamics of the localized “Worker,” the fermionic carrier of quantum information (Quni-Gudzinas, 2026a).

   from 2.1 The Signal-Worker Ontology

Where to read

1. A23 words · 1 min
2. Abstract170 words · 1 min
3. Keywords17 words · 1 min
4. 1.0 Introduction: The1,130 words · 5 min
5. 2.0 Theoretical1,181 words · 5 min
6. 3.01,157 words · 5 min
7. 4.01,077 words · 5 min
8. 5.0 Results709 words · 3 min
9. 6.0 Discussion: The644 words · 3 min
10. 7.0 Conclusion107 words · 1 min
11. Appendices1,939 words · 8 min