From Theory to Qibit: Designing Impossible Synthetic Molecules
Having emerged from a fairly intense decade-long research tunnel, I wanted to practically apply some of the theory I had been developing using a quantum computer. The notion of the superposition of all possible answers as a starting point for an optimization process attracted me, not to mention the fact that I had recently hosted the CEO and CDO of D-Wave at a Forbes quantum computing event, as a result of which I enrolled in a couple of D-Wave courses.
It has been a while since I programmed. I first needed to become familiar with the intricacies of Python and enhance my mathematical skills, particularly in manipulating vectors and matrices, as well as grasping basic probability and statistics, discrete mathematics—including sets, graphs, and combinatorial optimization—and optimization fundamentals like objective functions and constraints, which are essential for formulating problems in a manner suitable for quantum annealers to process. This was also my first experience programming a quantum computer. It required an understanding of Quadratic Unconstrained Binary Optimization (QUBO) modeling, the language used to interact with D-Wave’s hardware, and the practical aspects of embeddings, including knowledge of the unique Pegasus and Chimera graph topologies to effectively map problem graphs onto the quantum processing unit's (QPU) limited connectivity.
Quantum-Driven Molecular Design
I now faced the challenge of scoping out a problem that was both manageable and complex enough to justify using a quantum computer for optimization. I focused on designing a synthetic molecule composed of elements that, from a chemical standpoint, would be extremely difficult — or even impossible — to combine. Yet, if such a combination were feasible, it could lead to transformative materials and technologies: indestructible yet lightweight composites, high-energy batteries with inexhaustible capacity, or even room-temperature superconductors.
Central to this effort was a conceptual process I developed for combining the energetic imprints of elements via an algorithm and encoding these into removal hardware, aka programmable matter — a framework I elaborate in my forthcoming Springer Nature book, Pioneering New Avenues in Quantum Technology. The first step in this approach was to determine the optimal molecular design based on a range of objectives and constraints, drawing from a vast library of energetic imprints. To that end, I formulated a Quadratic Unconstrained Binary Optimization (QUBO) model and ran it on D-Wave’s quantum processing unit (QPU), enabling the system to compute an optimized configuration.
The modeling process and results are detailed in a paper accepted for publication by Springer Nature, and I will be presenting it at Imperial College London during the IEMTRONICS 2025 conference, from April 3 to 5. Below is the abstract from the paper:
Here’s a backup of the presentation I’ll deliver next week that summarizes the key ideas in the paper:
The idea of the “energetic imprint” expresses aspects of a ‘seed’ — a deterministic construct — envisioned to animate any quantum-object. In the Quaternary Interpretation of Quantum Dynamics (QIQD), reviewed in detail in Pioneering New Avenues in Quantum Technology (PNAQT), a qubit's primary purpose, rather than merely functioning as an information storage unit, would be to capture a four-dimensional state—potentially based on phase, amplitude, frequency, and polarization—from atom–light interactions. This process would extract the fourfold meaning embedded in atoms. The following graphic shows how the QIQD qubit (‘qibit’ to be exact) contrasts with superconducting, trapped ion, neutral atom, solid state spin, topological, DV photonic, and CV photonic qubits:
The fourfold meaning — hence the ‘quaternary’ in QIQD — is based on fourfold fractal patterns hypothesized to exist at multiple levels of granularity (refer to Cosmology of Light for more details) and is summarized in the following table:
Photonics Quantum Computing & Encoding Meaning
While the optimization process leading to the synthetic molecule — and the broader technological foundation laid out in PNAQT— are essential components of QIQD, an equally immediate and practical priority is the representation of fourfold meaning implicit in a quantum object within a qibit. To achieve this, light is envisioned as the interrogating medium — probing solid-state atoms to extract an element-specific quantum signature, or “meaning,” that is unique to each atomic species yet internally consistent across instances of the same element.
This quantum signature would likely be encoded into photonic states through a rich modulation process involving spectral, frequency, amplitude, phase, and polarization dynamics. The resulting photonic representation would then need to be maintained within a qibit, potentially realized through a hybrid qubit architecture — such as photonic-spin or superconducting-photonic platforms — that supports the required dimensional encoding.
Several emerging photonic quantum computing technologies offer promising avenues to achieve this vision. Here, I provide a brief review of Quandela, Photonic Inc., Xanadu, and PsiQuantum, each capable of employing unique light–matter interactions.
Quandela presents a logical fit through its use of quantum dots — nanoscale atomic structures embedded in semiconductors like InAs or GaAs — as single-photon sources. Light interacts with these quasi-atoms to extract quantum properties such as emission spectra, polarization, and spin. This architecture aligns well with the idea of extracting “meaning” from solid-state atoms. Quandela’s photonic platform supports a broad array of modulations: spectral tuning alters emission frequencies; frequency and amplitude modulation control photon intensity and timing; phase modulation is achieved through interferometry; and polarization modulation is intrinsic to single-photon behavior. Moreover, Quandela’s exploration of high-dimensional quantum states (qudits) suggests a compatibility with the multi-dimensional structure of the fourfold model.
Photonic Inc. operates within silicon-based solid-state systems, focusing on atomic spins embedded in defect centers such as T-centers. Photonic Inc. captures coherent and potentially entangled spin information by illuminating these spin states, effectively extracting “meaning.” Their spin-photon interface forms a link between solid-state atomic characteristics and photonic expression. Their infrastructure also appears to support the full suite of modulation techniques: spectral tuning for frequency control, frequency and amplitude modulation via integrated optics, phase shifting through precision modulators, and polarization manipulation using polarizing elements. This modulation toolkit provides the necessary flexibility to encode atomic signatures in a manner consistent with the fourfold framework.
Xanadu takes a photonic-first approach while maintaining compatibility with solid-state emitters like quantum dots and NV centers in diamond. While it does not directly probe atomic sources, Xanadu’s system can incorporate externally emitted photons already bearing atomic “meaning” — including spectral and spin-related data — into its photonic circuits. Its highly flexible modulation capabilities include spectral manipulation via frequency-bin encoding, amplitude and frequency adjustments through electro-optic modulators, phase tuning using integrated shifters, and polarization control through standard optical components. Xanadu’s continuous-variable (CV) architecture is especially noteworthy, offering an analog modality that can encode rich and subtle variations across all four dimensions — likely making it highly suited to the nuanced demands of QIQD.
PsiQuantum, though less directly focused on atomic interrogation, utilizes nonlinear optical effects in solid-state materials such as lithium niobate and silicon to generate photonic qubits. Light interacts with the material’s atomic lattice rather than individual atoms. Yet, the nonlinear response captures and embeds atomic-scale information — such as spectral and phase characteristics — into the emitted photons. PsiQuantum’s silicon-photonic platform supports spectral, frequency, amplitude, phase, and polarization modulation, also offering a medium for encoding derived atomic information in alignment with the fourfold model.
Conclusion
The test of theory through the optimization of a synthetic molecule marks only the beginning — a surface glimpse of a more profound journey: to reimagine quantum computing not merely as a mathematical engine but as a medium for capturing meaning — specifically, the fourfold energetic imprints embedded within atomic and even more complex atom-based structures.
From the molecule modeled on D-Wave’s quantum processing unit to the photonic architectures of Quandela, Photonic Inc., Xanadu, and PsiQuantum, each step brings us closer to encoding and manipulating the very essence of matter. These foundational efforts offer an early glimpse into what I call qibits — quantum units enriched with dimensional nuance — charting a path from abstract theoretical modeling to the creation of meaningful, technologically transformative quantum systems.
