Aerospace company Lockheed Martin (LMT) and tech firm IBM (IBM) recently used a new quantum method called sample-based quantum diagonalization (SQD) to simulate the molecule methylene (CH₂), making it the first time SQD has been used on an open-shell molecule. This is a big step forward because SQD could give quantum computers an advantage over classical computers for solving tough chemistry problems, especially those involving complex electron behavior that traditional methods struggle to handle.
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In their study, the scientists modeled the singlet and triplet electronic states of CH₂, which is important in things like combustion and atmospheric science. They ran the simulations on IBM’s 52-qubit quantum processor by using a hybrid setup that combines quantum and classical computing, and each test used up to 3,000 two-qubit gates. Interestingly, the SQD results were very accurate and closely matched what was expected from classical benchmarks known as Selected Configuration Interaction (SCI), especially in measuring bond energies and energy gaps between states.
It is worth noting that open-shell molecules like CH₂ are hard to study with classical computers because their unpaired electrons lead to complex interactions that require a lot of computing power. The SQD method helps by avoiding the need to fully rebuild the molecule’s wavefunction. Instead, it samples key values and uses quantum properties like electron entanglement to simplify the work. This successful test shows that quantum computing can be used for real chemical problems and could lead to better models for combustion reactions, chemical sensors, and new aerospace materials.
What Is the Target Price for IBM?
Turning to Wall Street, analysts have a Moderate Buy consensus rating on IBM stock based on eight Buys, five Holds, and two Sells assigned in the past three months, as indicated by the graphic below. Furthermore, the average IBM price target of $260.62 per share implies 0.9% upside potential.
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