Many Quantum devices are likely potential gravitational sensors too

Snowmass Media: 23. Quantum Computing Simulation for Collective Neutrino Oscillations – Valentina Amitrano at https://www.youtube.com/watch?v=xnkInU0hwHo

Valentina Amitrano,

Thank you, I was trying to understand neutrino oscillations. Your different perspective helped a lot. I got an update on qubits for free.

I do not know if anyone reads these comments. There ought to be a better way.

I am recommending to different qubit designers that they run them for days and weeks to check for sensitivity to gravitational tidal effects. Some of the designs are almost identical to purpose-built gravitational sensors. Almost anyone getting to where they build “good” quantum computers are also using the same methods and devices that are good for earth and solar system gravimetry and gravitational array imaging.

For reference, a superconducting gravimeter is roughly 0.1 nanometer/s^2 at 1 sample per second. It tracks only one axis of the tidal gravity. It cost about $250K But three axis MEMS gravimeters are basically 1 nm/s2 at 1 sps. They have a lot of drift, but only cost $250 if you make your own. Both can lock to the sun and moon for continuous calibration to have the whole network on one reference. There are dozens of ways now to track the sun and moon with gravitational sensors. It is nearly perfect Newtonian, and does not have the problems of ionospheric attenuation and changes. Works under the ocean and inside caves and shielded sites. With three axes, it is possible to solve for orientation of the sensor. Some of the broadband seismometers are sensitive enough to be classed as gravimeters. The transportable array had some instruments with no orientation data, but it is possible to solve for the orientation because the data only requires a linear regression for each axis. Three axes, 6 numbers. So only a little data is needed for continuous calibration. Once you lock down the big variations that effectively increases the sensitivity to small changes by about 100 fold. The residual is almost all atmospheric and ocean tidal effects, then cars, trucks people. With drones and cameras and machine vision to track traffic, that can be used to calibrate faster sensors. With time of flight sensors getting much cheaper, that means routine speed of gravity calibration.

The speed of light and gravity are identical, not close, identical. So all the frequencies and methods like “time of flight” that work for electromagnetism also work for gravitational signals. LIGO goes to a lot of trouble to suppress and limit Earth based gravitational signals. Calling it “Newtonian noise”. And they limit themselves to very tiny frequency band, avoiding the very strong local signals. I keep trying to tell them it is “Newtonian gravitational signals”, not noise. If is very likely that the local field is grainy at easily measurable levels. Certainly not down to Planck scale, and more like picometer and femtometer scale.

The Japan earthquake registered as a speed of light and gravity signal on both the superconducting gravimeter and the broadband seismometer networks. There are some efforts at earthquake early warning, but they need low cost imaging arrays too. So it comes down to finding groups who are working at anything “quantum”, “pico” and able to deal with complex signals over time. Anyone who has to deal with “earth tides” too. Accelerators, fission reactors, Big G experiments, fusion experiments, precise magnetic dipole moment, muon experiments. Lots of systems are sensitive now to gravitational changes. Everyone uses the same amplifiers, ADCs, processors and machine learning methods more and more.

Richard Collins, The Internet Foundation

SnowMass Media: 7-19 – CF: Paths To Discovery at https://www.youtube.com/watch?v=XwLUa6qKu6g

SnowMass Media,

The first hour of this video is blank. so go to 1:00:00 to see “Path to Dark Matter”. You can read the transcript (use the three dots and “show transcript”) to get a rough index of what is talked about. They just dumpled this video online and made no provision for adding video descriptions and links.

These verious potential projects and results and plans are not integrated into a global plan, and very narrow in self-selected participants. You all have to put as much effort into managing, advertising, communicating, documenting, recording and sharing as in idea generation and “work”.

This is another of millions of small groups where the players know each other, and make plans, but do not look at how the, sometimes, millions of people intereseted and tens of thousands working at least part time, will communicate and share.

There are some standard projects, some already well advanced, but SnowMass media did not provide links, maps, “gameboards” that let the 5 billion Internet users scan througjh quickly visually to see what is going on. A linear video that is 1:40:55 of actual content, is hard – to impossible — for most viewers to “see” as a wjhole. So you all have to use lists, links, purpose built websites, globally machine accessible datasets, and more effort, time and creativity – to overall management of what people can see and use and work on

It is possible to have global collaboration worksites that hundreds of millions can use for collaboration on global projects with billions of small steps, pieces, evernts, timelines, metrics, reports, visualizations, tools, data, results, priorities, purposes, goals, impacts, suppliers, beneficiaries, funding sources, supported projects.

Rather than making 5 billion (actually 8 billion eventually) humans all have to formulate a mental map of the topic of “SnowMass”, “Dark Matter” and the things you discuss here. You can learn how to do the “right” things and have the data, information, models, tools, groups and efforts laid out neatly and completely.

Richard Collins, The Internet Foundation

The transcript shows the full session, but no video for the first hour.

Bangalore Sathyaprakash – Cardiff University, Gravity Exploration Institute – https://profiles.cardiff.ac.uk/staff/sathyaprakashbs
Tiffany Lewis –
Angelina May – ??
Elise Nivitski –
Jamie Lewis Tom –

Many projects listed, no map, no links, no context. Good topic, bad internet methods