The best part is you could actually hear the aurora with your ears. I wondered how to record it for next time since 3664 now known as 3697 is coming back around

In Fairbanks you can actually hear them in real time.

I saw this on my phone as first alert, then came back to watch it on 4K computer. Amazing work as always on forward thinking that pretty much nobody else on Earth even considers. I was asked before were is our generations Einstein? Which is a great question and my answer is and always will be, David Mason.

@davidmason5755

11 күн бұрын

Thanks, Tom! It was an experiment that I had been wanting to conduct since the early 1980s. Fortunately, the Aurora was huge in Washington state on May 10th, and the years of monitoring sunspot activity paid off while having my equipment set up and ready for the event.

what an amazing video and great discovery. Thanks for sharing! You go David!

@davidmason5755

11 күн бұрын

Thank you! I'm glad you like it!

Reminds me of Forbidden Planet sounds

@davidmason5755

11 күн бұрын

Yes, and the great Leslie Nielsen was the star of that movie!

This is so awesome, David 💯

@davidmason5755

21 күн бұрын

Thank you, Jan!

I was hoping you were going to do this: yay!

@davidmason5755

20 күн бұрын

Thank you Nancy! I had mentioned my intention to record the sound of the Aurora to you after I had successfully recorded the sound from the modulated light from comet E3 ZTF. It was actually in the mid 1980s that I had the idea but I never had the opportunity until the recent Aurora event.

🥳

Did you use an ND filter on the PMT? I built a scintillation detector once and I was really nervous the first time I switched it on. Fortunately, it was more than adequately sealed. Now if only someone would figure out a way to record whistlers without the AC hum from the power lines in my back yard.. 😗

@davidmason5755

20 күн бұрын

That's a good question. I did not use a filter. The telescope used has an f-10 focal length so this attenuated the incoming light to the PMT and it was also at night. I slowly turned up the high voltage to avoid overcurrent and damage the PMT. There was a low level 60-120Hz signal detected in the spectrum analysis of the sound due to distant city light pollution.

I set the playback speed to 2X and could better hear the sounds you talk about. Would be cool to convert the colors to a stereo field representation. You’re going to have to buy yourself a Eurorack system :-).

@JohnLenardWalson

21 күн бұрын

dear david your excellent Scientific experiments hard work takes a lot of effort and time i know and value your papers witch are for sharing your own original research work with other scientists or for reviewing the research conducted by others. As such, they are critical to the evolution of modern science, in which the work of one scientist builds upon that of others. and record the sound data from light capture by optics of light frequency, have you ever try sound source code to produce frequency of light ? and any views of your experiment may hold any data in its audio that originally come from the light frequency

@davidmason5755

21 күн бұрын

I have not tried to alter the speed but I'm glad you were successful at hearing the strange parts by speeding up the audio and sharing that information. I presented the audio as it was recorded, and again with the described bandpass filtering.

@davidmason5755

21 күн бұрын

@@JohnLenardWalson I always conduct research in areas that have never been considered or explored. It's the only way to make new discoveries.

@JohnLenardWalson

21 күн бұрын

Playing the notes of DNA with light: extremely high frequency nano mechanical oscillations @barryklein1023 @davidmason5755 Dear david excerlant you have not alter the speed our friend hear thought it might of been (so this might mean he could hear a change in the frequency) i think your able to test the audio ? and find the frequency change, and just think if that each audio tone change has a note like F sharp or B flat possibly G ? You can also do all of the data processing, sonification, and even synchronize visuals @barryklein1023 @davidmason5755 Dear david excerlant you have not alter the speed but our youtube friend said he could hear what thought it might of been a change (so theroy this might mean he could hear a change in the frequency) i think your able to test the audio ? and find the frequency change, and just think if that each audio tone change has a note like C note is vibrating at the 256 or F sharp or B flat possibly G ? 528 Hz is one of the so-called Solfeggio frequencies. · The main Solfeggio frequencies are: · * 396 Hz - Liberating Guilt and Fear * 417 Hz -SORRY FOR CAPS LOCK ON STUCK. A FREQUENCY HUNTING BOX THAT COLLECTS DATA FROM ABOVE AND BELOW LIKE LIGHT AND OTHER PROPERTIES NO LIMITS TO COLLECTING DATA EVEN FROM THINGS WE CAN NOT SEE IN OUR SPECTRUM :) HUMANS ARE LIMITED TO SEE A HIDDEN WORLD OF FREQUENCIES SPECTRUM'S AND DIMENSIONS SO USE DATA COLLECTING BOX AVAILABLE, .Converting DNA sequences and particle vibrations into notes allows researchers to recognize unseen patterns and create songs witch i am doing finding the data and note and frequency The first step is to make sure you completely understand the data. What is it measuring? How was it collected? What does it all mean? Depending on your sonification, this stage may require some background research. import pandas as pd filename = 'lunarCraterAges' #name of csv data filedf = pd.read_csv(filename + '.csv') #load data as a pandas dataframedf.head() Then we’ll extract the age and diameter values and plot them import matplotlib.pylab as pltages = df['age'].values #get age values in an array diameters = df['diameter'].values #get diameter values in an arrayplt.scatter(ages, diameters, s=diameters) plt.xlabel('age [Myrs]') plt.ylabel('diameter [km]') plt.show() Since the x-axis measures age, time is running backwards in this plot. To get a better sense of how this data might unfold forwards in time, let’s convert the age measurements into time values, starting at 0 for the first impact in our data: times_myrs = max(ages) - ages #measure time from 1st impact in dataplt.scatter(times_myrs, diameters, s=diameters) plt.xlabel('time since impact 0 [Myrs]') plt.ylabel('diameter [km]') plt.show() Notice that there are many, many more smaller craters than large ones (bigger asteroid impacts are much more rare). You can also see that the rate increases over time. Most of this is due to a selection effect (it’s easier to date younger craters) but there is a statistically significant uptick around 290 million years ago. Interesting! This will also develop nicely as a piece of music since the tension will build over time and then resolve slightly at the very end. Mapping: Which data parameters are mapped to which auditory parameters? (Do crater sizes control the pitch of notes, or something else?)Mapping: Which data parameters are mapped to which auditory parameters? (Do crater sizes control the pitch of notes, or something else?) Polarity: What is the orientation of the mapping? (Do bigger craters produce higher or lower pitch notes?) Range: What range of each musical parameter will you choose? (How long will the piece be? What is the lowest and highest note?) Scaling (stretch/compress): Exactly how will numerical values be mapped from one range into another? (If a crater is twice as big should it be twice as loud? 4 times as loud? Something else?) Many audio parameters (such as pitch and volume) are not perceived linearly anyway so some non-linear stretching or compression is often helpful. Quantization: Will any of the data be rounded, how? (Will crater impacts be forced to occur ‘on beats’? Will pitches be rounded to notes from a certain scale?) More aggressive quantization may make it more musical but it also reduces the resolution. Crater ages will be mapped to time in the obvious way (happening forwards in time). Crater diameters will be mapped to musical pitch, with larger craters being lower pitched notes. You can make the opposite choice but I feel that this choice is more intuitive since larger objects/instruments can support lower notes. We will also use the crater diameters to control the note velocity (a combination of volume and intensity), with larger craters producing louder and more intense sounds (seems to make sense!). Try to identify the range, scaling, and quantization choices that are made as we implement the sonification design. Mapping, Mapping, Mapping… Mapping a set of numbers from one range to another is so common in sonification we might as well write a function that does just that for us. The following function will map input values (as an integer, float, or array) taken from one range, min_value to max_value, into a new range, min_result to max_result: def map_value(value, min_value, max_value, min_result, max_result): ‘’’maps value (or array of values) from one range to another’’’ result = min_result + (value - min_value)/(max_value - min_value)*(max_result - min_result) return result Note that this will return a float (or an array of floats) and we may need to round the result to an integer depending on what we’ll be doing with it. As an exercise, modify the function so that it will automatically round the result and return an integer if both min_result and max_result are integers. task is to compress time from over a billion years to under 1 minute. One way to do this is to set a conversion factor. Our time data is currently measured in millions of years. We’d like to compress it and express the result in beats. We’re mapping to beats, rather than seconds, because the MIDI file we’ll create later accepts time as being measured in beats. If we set a conversion factor of 25 million years per beat, we can just divide our times_myrs array by this factor. With this choice, the last note in the piece will land on beat 52.8. If we later set the tempo to be 60 beats per minute, then 1 beat will last for 1 second and the last note in our piece will play at exactly 52.8 seconds. This approach is useful if you want to add another element later that is synchronized to a certain unit of time. For example, playing a drum on every beat would indicate that 25 million years have passed, no matter what tempo you choose. myrs_per_beat = 25 #conversion factor: Myrs for each beat of musict_data = times_myrs/myrs_per_beat #compress impact times from Myrs to beats Option 2: Set a Duration

time ? date .. ?..

@davidmason5755

21 күн бұрын

The Aurora video and sound recording occurred on May 10th, 2024 in Washington State, about 10 miles east of Seattle. The time was between 10:00 to 11:30 PM.

@christophvonknobelsdorff1936

21 күн бұрын

@@davidmason5755 😘