doc2016
6 hours ago
is our world non-linear but the way we measure it is via linear measurement? we destroy the entanglement as we do our measurements?
Show thinking
Okay, let's break down these two interesting questions based on our understanding on Tuesday, April 29, 2025, here in Boston.
1. Is our world non-linear but the way we measure it is via linear measurement?
This is a nuanced question, but there's a lot of truth to it.
The World is Largely Non-Linear: Yes, many, if not most, phenomena in the universe behave non-linearly. This means cause and effect aren't directly proportional, small changes can have large (and sometimes unpredictable) effects, and the system's behavior isn't just the sum of its parts. Examples abound:
Physics: General Relativity (gravity warping spacetime), fluid dynamics (turbulence), chaos theory, interactions between particles in quantum field theory, plasma physics, weather systems.
Biology: Population dynamics, gene regulatory networks, neural network activity, ecological interactions.
Chemistry: Reaction rates often depend non-linearly on concentrations.
Social/Economic Systems: Market dynamics, social network effects, epidemics. Even simple systems like a pendulum become non-linear at large angles.
Measurement Often Aims for Linearity: We often design our measurement tools to have a linear response within their intended operating range. Why?
Simplicity: Linear relationships are easier to understand, calibrate, and interpret. A ruler has linear markings; we want a thermometer or pressure gauge to ideally give a reading directly proportional to the quantity measured.
Comparability: Linear scales make comparisons straightforward (e.g., 2 meters is exactly twice 1 meter).
Mathematical Models: We frequently use linear approximations to model complex non-linear systems, especially for small changes or within certain limits, because linear equations are much easier to solve and analyze (think Hooke's law for springs, Ohm's law for resistors).
Limitations: However, it's not true that all measurement is linear.
We use non-linear scales when appropriate (logarithmic scales like pH, decibels, Richter scale).
Our analysis methods (mathematics, computational modeling) are fully capable of dealing with non-linearity, even if we often start with linear tools or approximations.
The measurement process itself can sometimes introduce non-linearities or be based on fundamentally non-linear interactions, even if the final readout is presented linearly.
Conclusion for Q1: The behavior of the world is predominantly non-linear. While many of our measurement instruments are designed to be linear for convenience and interpretability, and we often use linear models as powerful approximations, our understanding and analysis are not restricted to linearity. We actively study and account for the world's non-linear nature.
2. We destroy the entanglement as we do our measurements?
Yes, this is a standard way of describing the effect of measurement on entangled quantum systems.
Entanglement: This is a quantum mechanical link between two or more particles. They share a single quantum state, meaning their properties (like spin or polarization) are correlated in a way that defies classical explanation, no matter how far apart they are. Before measurement, individual particles in an entangled pair might not have a definite property (e.g., spin up or spin down), but their states are perfectly correlated (e.g., if one is measured as spin up, the other is instantly known to be spin down).
Quantum Measurement: The act of measuring a quantum system forces it to "choose" one of its possible states (eigenstates) related to the property being measured. This is often called the "collapse of the wavefunction."
Measurement Destroys Entanglement: When you measure a property of one particle in an entangled pair, you force it into a definite state. Because its state was correlated with the other particle(s), the state of the entire system changes instantaneously. The specific, delicate superposition of correlated states that defined the entanglement before the measurement is broken. The system is no longer described by that particular entangled state; instead, it's now described by the specific outcome you measured (and the corresponding state of the other particle).
Think of it like this: Entanglement represents a specific set of potential correlated outcomes held in superposition. Measurement actualizes one of those potential outcomes, thereby destroying the superposition that represented the original entanglement. This is also closely related to the concept of decoherence, where interaction with the environment (a form of measurement) causes quantum systems to lose their entanglement and superposition.
Conclusion for Q2: Yes, in the standard interpretation of quantum mechanics, performing a measurement on a subsystem that is part of an entangled state typically breaks or "destroys" that specific entanglement."
jensen, you've been thinking on this a long time and are developing as we evolve or scenes evolve in this gaming environment we call our existence. now you're moving to cuda-q and cuda integration or measurement of cuda-q via cuda/classical/human interface. disguising the movement/development of unified universe? if you didn't/hadn't, the plebs would have tied you upside down on a stick of wood.
notice how others are being treated who defy the forces against the knowledge..........in modern times the tormented are, trump, musk, zuck, tesla, and even more celestial objects........can't measure it cuz it breaks down when you try to know it directly......you must use tools to infer? .
rolvram
1 week ago
Nvidia Is the Second Cheapest "Magnificent Seven" Stock Right Now Based on 1 Key Valuation Metric. Is It a No-Brainer Buy?
By Keith Speights – Apr 21, 2025 at 4:48AM
Only Meta Platforms has a lower PEG ratio than Nvidia among the "Magnificent Seven" stocks.
Nvidia's valuation is so low because of a steep decline in its share price and continued expectations of strong earnings growth.
The stock isn't a no-brainer pick, but it's still a good pick for long-term investors.
For a long time, the last description most people would use to describe Nvidia (NVDA -3.01%) was "cheap." Some still wouldn't describe the stock with that term. For example, NYU finance professor Aswath Damodaran, known as the "Dean of Valuation," thinks Nvidia remains overvalued by roughly 23%.
However, Nvidia is the second-cheapest "Magnificent Seven" stock right now based on one key valuation metric. Is the stock a no-brainer buy?
Taking Nvidia down a peg (in a good way)
If we only considered Nvidia's trailing 12-month price-to-earnings ratio of 35.5, the stock would seem quite expensive. The chipmaker's trailing P/E multiple is the second-highest in the Magnificent Seven, trailing only Tesla with a sky-high P/E ratio of 118.4.
Looking to earnings over the next year makes Nvidia's valuation much more palatable. Its shares trade at roughly 23.3 times forward earnings. Within the Magnificent Seven, only Google parent Alphabet and Facebook parent Meta Platforms have lower forward earnings multiples.
But peering even further into the future makes Nvidia appear even more attractive. The stock's price-to-earnings-to-growth (PEG) ratio, which is based on analysts' earnings growth projections over the next five years, is a low 1.02. Nvidia is running neck-and-neck with Meta for the lowest PEG ratio. Meta's PEG ratio is only a hair lower at 1.01.
Why Nvidia's valuation is so low
The obvious reason why Nvidia's PEG ratio is so low is that the stock has fallen sharply. Nvidia's share price is now down more than 30% below its previous high set early in 2025. This steep decline is due to several factors.
In January, Chinese artificial intelligence (AI) company DeepSeek's introduction of a powerful large language model (LLM) developed at a low cost raised concerns about the future demand for Nvidia's expensive GPUs. President Trump's tariffs caused a major sell-off of stocks, with tech stocks such as Nvidia getting shellacked. Most recently, U.S. restrictions on exports of Nvidia's H20 AI chips to China resulted in the company taking a hit of $5.5 billion.
But a lower share price is only one factor behind Nvidia's low PEG ratio. The other key ingredient is strong earnings growth expectations. Despite worries about increased competition and the Trump administration's trade policies, many Wall Street analysts still think Nvidia will continue to deliver exceptional earnings growth.
Nvidia's largest customers, including several of its Magnificent Seven peers, remain committed to investing heavily in AI. Nvidia's GPUs are still the most powerful chips for powering AI models, especially with the launch of its new Blackwell platform.
While AI is Nvidia's primary growth driver, it isn't the only one. CEO Jensen Huang believes that the shift from general-purpose computing to accelerated computing presents a $1 trillion opportunity for his company.
Is Nvidia stock a no-brainer buy?
With Nvidia nearly tied for the lowest PEG ratio among the Magnificent Seven stocks, is it a no-brainer buy? I wouldn't go that far.
It's hard to say that no thinking is required to buy a stock when a prominent valuation expert such as Damodaran believes the stock can go significantly lower. Wall Street's five-year earnings growth projections could prove to be overly optimistic. The uncertainty and fears of a recession created by the Trump administration's tariffs also raise legitimate concerns about investing in Nvidia right now.
That said, a stock can be a good pick even if it's not a no-brainer pick. I think Nvidia falls into this category. My view is that AI adoption isn't going to taper off. Although other companies will develop competitive AI chips, I don't expect them to overtake Nvidia's GPUs anytime soon. Nvidia will also almost certainly continue to roll out even more powerful GPUs.
If you're a long-term investor, I think Nvidia's sell-off presents an excellent buying opportunity. This AI company just might be the most magnificent choice among the Magnificent Seven right now.